Overview

Dataset statistics

Number of variables59
Number of observations53
Missing cells1127
Missing cells (%)36.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory24.6 KiB
Average record size in memory474.4 B

Variable types

Numeric12
Categorical38
Unsupported9

Alerts

type has constant value "regular" Constant
airdate has constant value "2020-12-12" Constant
_embedded.show.externals.tvrage has constant value "34149.0" Constant
url has a high cardinality: 53 distinct values High cardinality
_links.self.href has a high cardinality: 53 distinct values High cardinality
id is highly correlated with _embedded.show.idHigh correlation
season is highly correlated with rating.average and 2 other fieldsHigh correlation
number is highly correlated with _embedded.show.network.idHigh correlation
runtime is highly correlated with _embedded.show.runtime and 3 other fieldsHigh correlation
rating.average is highly correlated with season and 2 other fieldsHigh correlation
_embedded.show.id is highly correlated with id and 2 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 3 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with season and 9 other fieldsHigh correlation
_embedded.show.weight is highly correlated with _embedded.show.rating.average and 1 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with rating.average and 1 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 3 other fieldsHigh correlation
_embedded.show.updated is highly correlated with _embedded.show.rating.average and 1 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with number and 5 other fieldsHigh correlation
id is highly correlated with rating.averageHigh correlation
season is highly correlated with runtime and 4 other fieldsHigh correlation
number is highly correlated with rating.averageHigh correlation
runtime is highly correlated with season and 3 other fieldsHigh correlation
rating.average is highly correlated with id and 6 other fieldsHigh correlation
_embedded.show.id is highly correlated with rating.average and 3 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with season and 3 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with season and 3 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with season and 9 other fieldsHigh correlation
_embedded.show.weight is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with _embedded.show.rating.averageHigh correlation
_embedded.show.externals.thetvdb is highly correlated with rating.average and 3 other fieldsHigh correlation
_embedded.show.updated is highly correlated with _embedded.show.rating.averageHigh correlation
_embedded.show.network.id is highly correlated with _embedded.show.id and 2 other fieldsHigh correlation
season is highly correlated with rating.average and 1 other fieldsHigh correlation
runtime is highly correlated with _embedded.show.runtime and 2 other fieldsHigh correlation
rating.average is highly correlated with season and 1 other fieldsHigh correlation
_embedded.show.id is highly correlated with _embedded.show.rating.averageHigh correlation
_embedded.show.runtime is highly correlated with runtime and 3 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with season and 9 other fieldsHigh correlation
_embedded.show.weight is highly correlated with _embedded.show.rating.averageHigh correlation
_embedded.show.webChannel.id is highly correlated with _embedded.show.rating.averageHigh correlation
_embedded.show.externals.thetvdb is highly correlated with _embedded.show.rating.average and 1 other fieldsHigh correlation
_embedded.show.updated is highly correlated with _embedded.show.rating.average and 1 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with _embedded.show.runtime and 2 other fieldsHigh correlation
id is highly correlated with url and 36 other fieldsHigh correlation
url is highly correlated with id and 45 other fieldsHigh correlation
name is highly correlated with id and 43 other fieldsHigh correlation
season is highly correlated with id and 28 other fieldsHigh correlation
number is highly correlated with id and 18 other fieldsHigh correlation
airtime is highly correlated with url and 37 other fieldsHigh correlation
airstamp is highly correlated with id and 41 other fieldsHigh correlation
runtime is highly correlated with id and 37 other fieldsHigh correlation
summary is highly correlated with id and 42 other fieldsHigh correlation
rating.average is highly correlated with url and 30 other fieldsHigh correlation
_links.self.href is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.id is highly correlated with url and 34 other fieldsHigh correlation
_embedded.show.url is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.name is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.type is highly correlated with url and 37 other fieldsHigh correlation
_embedded.show.language is highly correlated with id and 36 other fieldsHigh correlation
_embedded.show.status is highly correlated with url and 30 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with id and 37 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with id and 39 other fieldsHigh correlation
_embedded.show.premiered is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.ended is highly correlated with id and 33 other fieldsHigh correlation
_embedded.show.officialSite is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.schedule.time is highly correlated with url and 35 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with url and 24 other fieldsHigh correlation
_embedded.show.weight is highly correlated with id and 30 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with id and 38 other fieldsHigh correlation
_embedded.show.webChannel.name is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.webChannel.country.name is highly correlated with id and 36 other fieldsHigh correlation
_embedded.show.webChannel.country.code is highly correlated with id and 36 other fieldsHigh correlation
_embedded.show.webChannel.country.timezone is highly correlated with id and 36 other fieldsHigh correlation
_embedded.show.webChannel.officialSite is highly correlated with id and 32 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with url and 28 other fieldsHigh correlation
_embedded.show.externals.imdb is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.image.medium is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.image.original is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.summary is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.updated is highly correlated with url and 35 other fieldsHigh correlation
_embedded.show._links.self.href is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show._links.previousepisode.href is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show._links.nextepisode.href is highly correlated with id and 31 other fieldsHigh correlation
image.medium is highly correlated with id and 42 other fieldsHigh correlation
image.original is highly correlated with id and 42 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with id and 32 other fieldsHigh correlation
_embedded.show.network.name is highly correlated with id and 37 other fieldsHigh correlation
_embedded.show.network.country.name is highly correlated with id and 33 other fieldsHigh correlation
_embedded.show.network.country.code is highly correlated with id and 33 other fieldsHigh correlation
_embedded.show.network.country.timezone is highly correlated with id and 33 other fieldsHigh correlation
runtime has 4 (7.5%) missing values Missing
image has 53 (100.0%) missing values Missing
summary has 36 (67.9%) missing values Missing
rating.average has 49 (92.5%) missing values Missing
_embedded.show.runtime has 14 (26.4%) missing values Missing
_embedded.show.averageRuntime has 5 (9.4%) missing values Missing
_embedded.show.ended has 32 (60.4%) missing values Missing
_embedded.show.officialSite has 5 (9.4%) missing values Missing
_embedded.show.rating.average has 49 (92.5%) missing values Missing
_embedded.show.network has 53 (100.0%) missing values Missing
_embedded.show.webChannel.id has 3 (5.7%) missing values Missing
_embedded.show.webChannel.name has 3 (5.7%) missing values Missing
_embedded.show.webChannel.country.name has 24 (45.3%) missing values Missing
_embedded.show.webChannel.country.code has 24 (45.3%) missing values Missing
_embedded.show.webChannel.country.timezone has 24 (45.3%) missing values Missing
_embedded.show.webChannel.officialSite has 31 (58.5%) missing values Missing
_embedded.show.dvdCountry has 53 (100.0%) missing values Missing
_embedded.show.externals.tvrage has 51 (96.2%) missing values Missing
_embedded.show.externals.thetvdb has 15 (28.3%) missing values Missing
_embedded.show.externals.imdb has 30 (56.6%) missing values Missing
_embedded.show.image.medium has 3 (5.7%) missing values Missing
_embedded.show.image.original has 3 (5.7%) missing values Missing
_embedded.show.summary has 2 (3.8%) missing values Missing
_embedded.show._links.nextepisode.href has 49 (92.5%) missing values Missing
image.medium has 35 (66.0%) missing values Missing
image.original has 35 (66.0%) missing values Missing
_embedded.show.image has 53 (100.0%) missing values Missing
_embedded.show.network.id has 46 (86.8%) missing values Missing
_embedded.show.network.name has 46 (86.8%) missing values Missing
_embedded.show.network.country.name has 46 (86.8%) missing values Missing
_embedded.show.network.country.code has 46 (86.8%) missing values Missing
_embedded.show.network.country.timezone has 46 (86.8%) missing values Missing
_embedded.show.network.officialSite has 53 (100.0%) missing values Missing
_embedded.show.webChannel has 53 (100.0%) missing values Missing
_embedded.show.webChannel.country has 53 (100.0%) missing values Missing
url is uniformly distributed Uniform
name is uniformly distributed Uniform
summary is uniformly distributed Uniform
rating.average is uniformly distributed Uniform
_links.self.href is uniformly distributed Uniform
_embedded.show.url is uniformly distributed Uniform
_embedded.show.name is uniformly distributed Uniform
_embedded.show.officialSite is uniformly distributed Uniform
_embedded.show.externals.imdb is uniformly distributed Uniform
_embedded.show.image.medium is uniformly distributed Uniform
_embedded.show.image.original is uniformly distributed Uniform
_embedded.show.summary is uniformly distributed Uniform
_embedded.show._links.self.href is uniformly distributed Uniform
_embedded.show._links.previousepisode.href is uniformly distributed Uniform
_embedded.show._links.nextepisode.href is uniformly distributed Uniform
image.medium is uniformly distributed Uniform
image.original is uniformly distributed Uniform
id has unique values Unique
url has unique values Unique
_links.self.href has unique values Unique
image is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.genres is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.schedule.days is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.network is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.dvdCountry is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.image is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.network.officialSite is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel.country is an unsupported type, check if it needs cleaning or further analysis Unsupported

Reproduction

Analysis started2022-09-06 02:41:33.015050
Analysis finished2022-09-06 02:41:52.849677
Duration19.83 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct53
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2058288.415
Minimum1943280
Maximum2386106
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size552.0 B
2022-09-05T21:41:52.961188image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1943280
5-th percentile1961749
Q11981088
median1988859
Q32113320
95-th percentile2313968.6
Maximum2386106
Range442826
Interquartile range (IQR)132232

Descriptive statistics

Standard deviation119068.8302
Coefficient of variation (CV)0.05784846735
Kurtosis0.7547929899
Mean2058288.415
Median Absolute Deviation (MAD)21791
Skewness1.379630982
Sum109089286
Variance1.417738632 × 1010
MonotonicityNot monotonic
2022-09-05T21:41:53.092475image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19888591
 
1.9%
19861561
 
1.9%
19861581
 
1.9%
20000581
 
1.9%
20000591
 
1.9%
20399361
 
1.9%
21102461
 
1.9%
21817961
 
1.9%
22893211
 
1.9%
23181021
 
1.9%
Other values (43)43
81.1%
ValueCountFrequency (%)
19432801
1.9%
19537881
1.9%
19612871
1.9%
19620571
1.9%
19670681
1.9%
19719391
1.9%
19719401
1.9%
19723461
1.9%
19725651
1.9%
19725661
1.9%
ValueCountFrequency (%)
23861061
1.9%
23476791
1.9%
23181021
1.9%
23112131
1.9%
23035401
1.9%
22893211
1.9%
22121661
1.9%
21868681
1.9%
21821171
1.9%
21817961
1.9%

url
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct53
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size552.0 B
https://www.tvmaze.com/episodes/1988859/sim-for-you-4x21-chanyeols-episode-21
 
1
https://www.tvmaze.com/episodes/1986156/the-burning-river-1x06-episode-6
 
1
https://www.tvmaze.com/episodes/1986158/the-burning-river-1x08-episode-8
 
1
https://www.tvmaze.com/episodes/2000058/ultimate-note-1x11-episode-11
 
1
https://www.tvmaze.com/episodes/2000059/ultimate-note-1x12-episode-12
 
1
Other values (48)
48 

Length

Max length122
Median length94
Mean length81.22641509
Min length58

Characters and Unicode

Total characters4305
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique53 ?
Unique (%)100.0%

Sample

1st rowhttps://www.tvmaze.com/episodes/1988859/sim-for-you-4x21-chanyeols-episode-21
2nd rowhttps://www.tvmaze.com/episodes/1986140/soul-land-7x04-di134ji
3rd rowhttps://www.tvmaze.com/episodes/2386106/xian-feng-jian-yu-lu-1x47-episode-47
4th rowhttps://www.tvmaze.com/episodes/2138925/tokyo-joshi-pro-wrestling-2020-12-12-tjpw-fall-tour-20-womm-wrestling-of-my-mind
5th rowhttps://www.tvmaze.com/episodes/1962057/heaven-officials-blessing-1x08-foreboding-wind-of-the-ancient-country

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1988859/sim-for-you-4x21-chanyeols-episode-211
 
1.9%
https://www.tvmaze.com/episodes/1986156/the-burning-river-1x06-episode-61
 
1.9%
https://www.tvmaze.com/episodes/1986158/the-burning-river-1x08-episode-81
 
1.9%
https://www.tvmaze.com/episodes/2000058/ultimate-note-1x11-episode-111
 
1.9%
https://www.tvmaze.com/episodes/2000059/ultimate-note-1x12-episode-121
 
1.9%
https://www.tvmaze.com/episodes/2039936/tregayes-way-in-the-kitchen-1x05-taco-night-any-night1
 
1.9%
https://www.tvmaze.com/episodes/2110246/paranormal-nightmare-5x06-a-haunting-in-west-virginia1
 
1.9%
https://www.tvmaze.com/episodes/2181796/i-like-to-watch-3x08-selena-the-series1
 
1.9%
https://www.tvmaze.com/episodes/2289321/blippi-2020-12-12-blippi-goes-indoor-skydiving-fun-and-educational-videos-for-kids1
 
1.9%
https://www.tvmaze.com/episodes/2318102/bride-of-beirut-2x46-episode-461
 
1.9%
Other values (43)43
81.1%

Length

2022-09-05T21:41:53.205930image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1988859/sim-for-you-4x21-chanyeols-episode-211
 
1.9%
https://www.tvmaze.com/episodes/1986140/soul-land-7x04-di134ji1
 
1.9%
https://www.tvmaze.com/episodes/2386106/xian-feng-jian-yu-lu-1x47-episode-471
 
1.9%
https://www.tvmaze.com/episodes/2138925/tokyo-joshi-pro-wrestling-2020-12-12-tjpw-fall-tour-20-womm-wrestling-of-my-mind1
 
1.9%
https://www.tvmaze.com/episodes/1962057/heaven-officials-blessing-1x08-foreboding-wind-of-the-ancient-country1
 
1.9%
https://www.tvmaze.com/episodes/1972565/the-wolf-1x23-episode-231
 
1.9%
https://www.tvmaze.com/episodes/1972566/the-wolf-1x24-episode-241
 
1.9%
https://www.tvmaze.com/episodes/1998578/mr-right-is-here-1x07-episode-71
 
1.9%
https://www.tvmaze.com/episodes/1998579/mr-right-is-here-1x08-episode-81
 
1.9%
https://www.tvmaze.com/episodes/2113320/klassen-3x18-herman-dahl-tar-over1
 
1.9%
Other values (43)43
81.1%

Most occurring characters

ValueCountFrequency (%)
e354
 
8.2%
-352
 
8.2%
/265
 
6.2%
s256
 
5.9%
t255
 
5.9%
o227
 
5.3%
w190
 
4.4%
i177
 
4.1%
a154
 
3.6%
m153
 
3.6%
Other values (30)1922
44.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2879
66.9%
Decimal Number650
 
15.1%
Other Punctuation424
 
9.8%
Dash Punctuation352
 
8.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e354
12.3%
s256
 
8.9%
t255
 
8.9%
o227
 
7.9%
w190
 
6.6%
i177
 
6.1%
a154
 
5.3%
m153
 
5.3%
p149
 
5.2%
d117
 
4.1%
Other values (16)847
29.4%
Decimal Number
ValueCountFrequency (%)
1151
23.2%
2112
17.2%
086
13.2%
956
 
8.6%
850
 
7.7%
744
 
6.8%
644
 
6.8%
438
 
5.8%
335
 
5.4%
534
 
5.2%
Other Punctuation
ValueCountFrequency (%)
/265
62.5%
.106
 
25.0%
:53
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-352
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2879
66.9%
Common1426
33.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e354
12.3%
s256
 
8.9%
t255
 
8.9%
o227
 
7.9%
w190
 
6.6%
i177
 
6.1%
a154
 
5.3%
m153
 
5.3%
p149
 
5.2%
d117
 
4.1%
Other values (16)847
29.4%
Common
ValueCountFrequency (%)
-352
24.7%
/265
18.6%
1151
10.6%
2112
 
7.9%
.106
 
7.4%
086
 
6.0%
956
 
3.9%
:53
 
3.7%
850
 
3.5%
744
 
3.1%
Other values (4)151
10.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII4305
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e354
 
8.2%
-352
 
8.2%
/265
 
6.2%
s256
 
5.9%
t255
 
5.9%
o227
 
5.3%
w190
 
4.4%
i177
 
4.1%
a154
 
3.6%
m153
 
3.6%
Other values (30)1922
44.6%

name
Categorical

HIGH CORRELATION
UNIFORM

Distinct48
Distinct (%)90.6%
Missing0
Missing (%)0.0%
Memory size552.0 B
Episode 6
 
3
Episode 7
 
2
Episode 8
 
2
Episode 12
 
2
Chanyeol's Episode 21
 
1
Other values (43)
43 

Length

Max length66
Median length44
Mean length18.35849057
Min length5

Characters and Unicode

Total characters973
Distinct characters87
Distinct categories10 ?
Distinct scripts5 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)83.0%

Sample

1st rowChanyeol's Episode 21
2nd row第134集
3rd rowEpisode 47
4th rowTJPW Fall Tour '20 ~ WOMM (Wrestling Of My Mind) ~
5th rowForeboding Wind of the Ancient Country

Common Values

ValueCountFrequency (%)
Episode 63
 
5.7%
Episode 72
 
3.8%
Episode 82
 
3.8%
Episode 122
 
3.8%
Chanyeol's Episode 211
 
1.9%
"The Dark Eaters"1
 
1.9%
Taco Night, Any Night1
 
1.9%
A Haunting in West Virginia1
 
1.9%
Selena: The Series1
 
1.9%
Blippi Goes Indoor Skydiving | Fun and Educational Videos For Kids1
 
1.9%
Other values (38)38
71.7%

Length

2022-09-05T21:41:53.356203image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
episode18
 
9.7%
the7
 
3.8%
6
 
3.2%
75
 
2.7%
124
 
2.2%
of4
 
2.2%
63
 
1.6%
december3
 
1.6%
12
 
1.1%
del2
 
1.1%
Other values (118)131
70.8%

Most occurring characters

ValueCountFrequency (%)
132
 
13.6%
e82
 
8.4%
o62
 
6.4%
i56
 
5.8%
r48
 
4.9%
s40
 
4.1%
d39
 
4.0%
a39
 
4.0%
n38
 
3.9%
t32
 
3.3%
Other values (77)405
41.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter607
62.4%
Space Separator132
 
13.6%
Uppercase Letter125
 
12.8%
Decimal Number68
 
7.0%
Other Punctuation19
 
2.0%
Other Letter14
 
1.4%
Dash Punctuation3
 
0.3%
Math Symbol3
 
0.3%
Close Punctuation1
 
0.1%
Open Punctuation1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e82
13.5%
o62
10.2%
i56
 
9.2%
r48
 
7.9%
s40
 
6.6%
d39
 
6.4%
a39
 
6.4%
n38
 
6.3%
t32
 
5.3%
l28
 
4.6%
Other values (17)143
23.6%
Uppercase Letter
ValueCountFrequency (%)
E21
16.8%
T11
 
8.8%
F10
 
8.0%
C9
 
7.2%
D8
 
6.4%
M8
 
6.4%
P8
 
6.4%
W7
 
5.6%
S7
 
5.6%
A6
 
4.8%
Other values (13)30
24.0%
Other Letter
ValueCountFrequency (%)
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
Other values (4)4
28.6%
Decimal Number
ValueCountFrequency (%)
118
26.5%
214
20.6%
48
11.8%
76
 
8.8%
66
 
8.8%
54
 
5.9%
04
 
5.9%
93
 
4.4%
33
 
4.4%
82
 
2.9%
Other Punctuation
ValueCountFrequency (%)
,5
26.3%
.4
21.1%
:4
21.1%
"2
 
10.5%
'2
 
10.5%
?1
 
5.3%
!1
 
5.3%
Math Symbol
ValueCountFrequency (%)
~2
66.7%
|1
33.3%
Space Separator
ValueCountFrequency (%)
132
100.0%
Dash Punctuation
ValueCountFrequency (%)
-3
100.0%
Close Punctuation
ValueCountFrequency (%)
)1
100.0%
Open Punctuation
ValueCountFrequency (%)
(1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin727
74.7%
Common227
 
23.3%
Hangul12
 
1.2%
Cyrillic5
 
0.5%
Han2
 
0.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e82
 
11.3%
o62
 
8.5%
i56
 
7.7%
r48
 
6.6%
s40
 
5.5%
d39
 
5.4%
a39
 
5.4%
n38
 
5.2%
t32
 
4.4%
l28
 
3.9%
Other values (35)263
36.2%
Common
ValueCountFrequency (%)
132
58.1%
118
 
7.9%
214
 
6.2%
48
 
3.5%
76
 
2.6%
66
 
2.6%
,5
 
2.2%
.4
 
1.8%
54
 
1.8%
04
 
1.8%
Other values (13)26
 
11.5%
Hangul
ValueCountFrequency (%)
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
Other values (2)2
16.7%
Cyrillic
ValueCountFrequency (%)
я1
20.0%
и1
20.0%
р1
20.0%
е1
20.0%
с1
20.0%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII954
98.0%
Hangul12
 
1.2%
Cyrillic5
 
0.5%
CJK2
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
132
 
13.8%
e82
 
8.6%
o62
 
6.5%
i56
 
5.9%
r48
 
5.0%
s40
 
4.2%
d39
 
4.1%
a39
 
4.1%
n38
 
4.0%
t32
 
3.4%
Other values (58)386
40.5%
Hangul
ValueCountFrequency (%)
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
Other values (2)2
16.7%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%
Cyrillic
ValueCountFrequency (%)
я1
20.0%
и1
20.0%
р1
20.0%
е1
20.0%
с1
20.0%

season
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct10
Distinct (%)18.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean344.9056604
Minimum1
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size552.0 B
2022-09-05T21:41:53.569207image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q36
95-th percentile2020
Maximum2020
Range2019
Interquartile range (IQR)5

Descriptive statistics

Standard deviation764.8430021
Coefficient of variation (CV)2.217542621
Kurtosis1.326351822
Mean344.9056604
Median Absolute Deviation (MAD)0
Skewness1.81042903
Sum18280
Variance584984.8179
MonotonicityNot monotonic
2022-09-05T21:41:53.837374image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
131
58.5%
20209
 
17.0%
34
 
7.5%
102
 
3.8%
52
 
3.8%
41
 
1.9%
71
 
1.9%
21
 
1.9%
81
 
1.9%
61
 
1.9%
ValueCountFrequency (%)
131
58.5%
21
 
1.9%
34
 
7.5%
41
 
1.9%
52
 
3.8%
61
 
1.9%
71
 
1.9%
81
 
1.9%
102
 
3.8%
20209
 
17.0%
ValueCountFrequency (%)
20209
 
17.0%
102
 
3.8%
81
 
1.9%
71
 
1.9%
61
 
1.9%
52
 
3.8%
41
 
1.9%
34
 
7.5%
21
 
1.9%
131
58.5%

number
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct27
Distinct (%)50.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.62264151
Minimum1
Maximum339
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size552.0 B
2022-09-05T21:41:54.059578image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q16
median8
Q316
95-th percentile49
Maximum339
Range338
Interquartile range (IQR)10

Descriptive statistics

Standard deviation46.48375498
Coefficient of variation (CV)2.368883668
Kurtosis44.94077918
Mean19.62264151
Median Absolute Deviation (MAD)4
Skewness6.489509156
Sum1040
Variance2160.739478
MonotonicityNot monotonic
2022-09-05T21:41:54.175090image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
65
 
9.4%
85
 
9.4%
45
 
9.4%
75
 
9.4%
53
 
5.7%
113
 
5.7%
143
 
5.7%
32
 
3.8%
132
 
3.8%
122
 
3.8%
Other values (17)18
34.0%
ValueCountFrequency (%)
11
 
1.9%
21
 
1.9%
32
 
3.8%
45
9.4%
53
5.7%
65
9.4%
75
9.4%
85
9.4%
91
 
1.9%
113
5.7%
ValueCountFrequency (%)
3391
1.9%
531
1.9%
521
1.9%
471
1.9%
461
1.9%
431
1.9%
242
3.8%
231
1.9%
211
1.9%
191
1.9%

type
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size552.0 B
regular
53 

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters371
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowregular
2nd rowregular
3rd rowregular
4th rowregular
5th rowregular

Common Values

ValueCountFrequency (%)
regular53
100.0%

Length

2022-09-05T21:41:54.270197image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:41:54.351499image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
regular53
100.0%

Most occurring characters

ValueCountFrequency (%)
r106
28.6%
e53
14.3%
g53
14.3%
u53
14.3%
l53
14.3%
a53
14.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter371
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r106
28.6%
e53
14.3%
g53
14.3%
u53
14.3%
l53
14.3%
a53
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin371
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
r106
28.6%
e53
14.3%
g53
14.3%
u53
14.3%
l53
14.3%
a53
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII371
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r106
28.6%
e53
14.3%
g53
14.3%
u53
14.3%
l53
14.3%
a53
14.3%

airdate
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size552.0 B
2020-12-12
53 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters530
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-12
2nd row2020-12-12
3rd row2020-12-12
4th row2020-12-12
5th row2020-12-12

Common Values

ValueCountFrequency (%)
2020-12-1253
100.0%

Length

2022-09-05T21:41:54.423733image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:41:54.510695image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-1253
100.0%

Most occurring characters

ValueCountFrequency (%)
2212
40.0%
0106
20.0%
-106
20.0%
1106
20.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number424
80.0%
Dash Punctuation106
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2212
50.0%
0106
25.0%
1106
25.0%
Dash Punctuation
ValueCountFrequency (%)
-106
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common530
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2212
40.0%
0106
20.0%
-106
20.0%
1106
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII530
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2212
40.0%
0106
20.0%
-106
20.0%
1106
20.0%

airtime
Categorical

HIGH CORRELATION

Distinct15
Distinct (%)28.3%
Missing0
Missing (%)0.0%
Memory size552.0 B
30 
20:00
06:00
 
2
10:00
 
2
12:00
 
2
Other values (10)
12 

Length

Max length5
Median length0
Mean length2.169811321
Min length0

Characters and Unicode

Total characters115
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)15.1%

Sample

1st row06:00
2nd row10:00
3rd row10:00
4th row12:00
5th row11:00

Common Values

ValueCountFrequency (%)
30
56.6%
20:005
 
9.4%
06:002
 
3.8%
10:002
 
3.8%
12:002
 
3.8%
11:002
 
3.8%
21:002
 
3.8%
05:001
 
1.9%
17:001
 
1.9%
18:001
 
1.9%
Other values (5)5
 
9.4%

Length

2022-09-05T21:41:54.582181image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20:005
21.7%
06:002
 
8.7%
10:002
 
8.7%
12:002
 
8.7%
11:002
 
8.7%
21:002
 
8.7%
05:001
 
4.3%
17:001
 
4.3%
18:001
 
4.3%
00:001
 
4.3%
Other values (4)4
17.4%

Most occurring characters

ValueCountFrequency (%)
055
47.8%
:23
20.0%
116
 
13.9%
211
 
9.6%
54
 
3.5%
63
 
2.6%
71
 
0.9%
81
 
0.9%
91
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number92
80.0%
Other Punctuation23
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
055
59.8%
116
 
17.4%
211
 
12.0%
54
 
4.3%
63
 
3.3%
71
 
1.1%
81
 
1.1%
91
 
1.1%
Other Punctuation
ValueCountFrequency (%)
:23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common115
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
055
47.8%
:23
20.0%
116
 
13.9%
211
 
9.6%
54
 
3.5%
63
 
2.6%
71
 
0.9%
81
 
0.9%
91
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII115
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
055
47.8%
:23
20.0%
116
 
13.9%
211
 
9.6%
54
 
3.5%
63
 
2.6%
71
 
0.9%
81
 
0.9%
91
 
0.9%

airstamp
Categorical

HIGH CORRELATION

Distinct19
Distinct (%)35.8%
Missing0
Missing (%)0.0%
Memory size552.0 B
2020-12-12T12:00:00+00:00
21 
2020-12-12T17:00:00+00:00
2020-12-12T04:00:00+00:00
2020-12-12T11:00:00+00:00
2020-12-12T02:00:00+00:00
 
2
Other values (14)
16 

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters1325
Distinct characters14
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)22.6%

Sample

1st row2020-12-11T21:00:00+00:00
2nd row2020-12-12T02:00:00+00:00
3rd row2020-12-12T02:00:00+00:00
4th row2020-12-12T03:00:00+00:00
5th row2020-12-12T03:00:00+00:00

Common Values

ValueCountFrequency (%)
2020-12-12T12:00:00+00:0021
39.6%
2020-12-12T17:00:00+00:006
 
11.3%
2020-12-12T04:00:00+00:005
 
9.4%
2020-12-12T11:00:00+00:003
 
5.7%
2020-12-12T02:00:00+00:002
 
3.8%
2020-12-13T02:00:00+00:002
 
3.8%
2020-12-12T03:00:00+00:002
 
3.8%
2020-12-12T08:00:00+00:001
 
1.9%
2020-12-12T09:00:00+00:001
 
1.9%
2020-12-12T07:00:00+00:001
 
1.9%
Other values (9)9
17.0%

Length

2022-09-05T21:41:54.661563image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-12t12:00:00+00:0021
39.6%
2020-12-12t17:00:00+00:006
 
11.3%
2020-12-12t04:00:00+00:005
 
9.4%
2020-12-12t11:00:00+00:003
 
5.7%
2020-12-12t02:00:00+00:002
 
3.8%
2020-12-13t02:00:00+00:002
 
3.8%
2020-12-12t03:00:00+00:002
 
3.8%
2020-12-12t15:15:00+00:001
 
1.9%
2020-12-12t21:15:00+00:001
 
1.9%
2020-12-12t21:00:00+00:001
 
1.9%
Other values (9)9
17.0%

Most occurring characters

ValueCountFrequency (%)
0540
40.8%
2237
17.9%
:159
 
12.0%
1150
 
11.3%
-106
 
8.0%
T53
 
4.0%
+53
 
4.0%
77
 
0.5%
56
 
0.5%
45
 
0.4%
Other values (4)9
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number954
72.0%
Other Punctuation159
 
12.0%
Dash Punctuation106
 
8.0%
Uppercase Letter53
 
4.0%
Math Symbol53
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0540
56.6%
2237
24.8%
1150
 
15.7%
77
 
0.7%
56
 
0.6%
45
 
0.5%
35
 
0.5%
82
 
0.2%
91
 
0.1%
61
 
0.1%
Other Punctuation
ValueCountFrequency (%)
:159
100.0%
Dash Punctuation
ValueCountFrequency (%)
-106
100.0%
Uppercase Letter
ValueCountFrequency (%)
T53
100.0%
Math Symbol
ValueCountFrequency (%)
+53
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1272
96.0%
Latin53
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0540
42.5%
2237
18.6%
:159
 
12.5%
1150
 
11.8%
-106
 
8.3%
+53
 
4.2%
77
 
0.6%
56
 
0.5%
45
 
0.4%
35
 
0.4%
Other values (3)4
 
0.3%
Latin
ValueCountFrequency (%)
T53
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1325
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0540
40.8%
2237
17.9%
:159
 
12.0%
1150
 
11.3%
-106
 
8.0%
T53
 
4.0%
+53
 
4.0%
77
 
0.5%
56
 
0.5%
45
 
0.4%
Other values (4)9
 
0.7%

runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct26
Distinct (%)53.1%
Missing4
Missing (%)7.5%
Infinite0
Infinite (%)0.0%
Mean41.85714286
Minimum5
Maximum180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size552.0 B
2022-09-05T21:41:54.742297image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile12.8
Q120
median44
Q345
95-th percentile110
Maximum180
Range175
Interquartile range (IQR)25

Descriptive statistics

Standard deviation32.51153641
Coefficient of variation (CV)0.7767261259
Kurtosis6.549469766
Mean41.85714286
Median Absolute Deviation (MAD)19
Skewness2.236802611
Sum2051
Variance1057
MonotonicityNot monotonic
2022-09-05T21:41:54.846640image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
4512
22.6%
604
 
7.5%
203
 
5.7%
162
 
3.8%
152
 
3.8%
142
 
3.8%
302
 
3.8%
192
 
3.8%
1202
 
3.8%
252
 
3.8%
Other values (16)16
30.2%
(Missing)4
 
7.5%
ValueCountFrequency (%)
51
 
1.9%
81
 
1.9%
121
 
1.9%
142
3.8%
152
3.8%
162
3.8%
192
3.8%
203
5.7%
211
 
1.9%
221
 
1.9%
ValueCountFrequency (%)
1801
 
1.9%
1202
 
3.8%
951
 
1.9%
891
 
1.9%
604
 
7.5%
521
 
1.9%
481
 
1.9%
471
 
1.9%
4512
22.6%
441
 
1.9%

image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing53
Missing (%)100.0%
Memory size552.0 B

summary
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct17
Distinct (%)100.0%
Missing36
Missing (%)67.9%
Memory size552.0 B
<p><b>#LastNightOfSummerVacation #10PointsOutof10 #TheRevealoftheFinalGift</b></p>
 
1
<p>lzel, K'in and Yun head towards the second gate at Lakamha, where they encounter a warrior looking to bargain.</p>
 
1
<p>Finale! The last three participants will go through the finals and gold finals. Tonight we are left with one winner and three revelations! Did you guess correctly?</p>
 
1
<p>It's game night, so Chef Lovely's making her famous Fried Chicken Sliders with a Creamy Scallion Slaw, Shrimp and Crab Cakes with a Spicy Citrus Remoulade and "Love Cookies" inspired by her Auntie Faye.</p>
 
1
<p><b>Brennan, Ify, and Ally play a simple, regular game of Jeopardy!</b></p>
 
1
Other values (12)
12 

Length

Max length402
Median length174
Mean length182.7058824
Min length18

Characters and Unicode

Total characters3106
Distinct characters72
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)100.0%

Sample

1st row<p><b>#LastNightOfSummerVacation #10PointsOutof10 #TheRevealoftheFinalGift</b></p>
2nd row<p>Mount Olympus is under attack and the young deities must face two giants: The Aloads brothers. Athena, Zeus, Poseidon and Hades are fighting against them, while the other Olympians seek help from the Titans. Who set the giants free from Tartarus in the Underworld ? Will the gods's divine power be enough to defeat their enemies ?</p>
3rd row<p>Mawin comes home drunk after learning the news about his audition results.  Tops treats Marwin's injury to his forehead and prepares him a meal to help him sober up.  </p>
4th row<p>The Japanese launch attacks all over Southeast Asia and the Pacific, and launch a preemptive surprise attack on the American Pacific Fleet at Pearl Harbor. The war is suddenly much larger. In the USSR, the Germans find themselves now heavily on the defensive after the failure to take Moscow, while in North Africa, Erwin Rommel decides he must withdraw out of Cyrenaica to await reinforcements.</p>
5th row<p>Tan initiates a bold move to make his feelings clear.  </p>

Common Values

ValueCountFrequency (%)
<p><b>#LastNightOfSummerVacation #10PointsOutof10 #TheRevealoftheFinalGift</b></p>1
 
1.9%
<p>lzel, K'in and Yun head towards the second gate at Lakamha, where they encounter a warrior looking to bargain.</p>1
 
1.9%
<p>Finale! The last three participants will go through the finals and gold finals. Tonight we are left with one winner and three revelations! Did you guess correctly?</p>1
 
1.9%
<p>It's game night, so Chef Lovely's making her famous Fried Chicken Sliders with a Creamy Scallion Slaw, Shrimp and Crab Cakes with a Spicy Citrus Remoulade and "Love Cookies" inspired by her Auntie Faye.</p>1
 
1.9%
<p><b>Brennan, Ify, and Ally play a simple, regular game of Jeopardy!</b></p>1
 
1.9%
<p>It's time. </p>1
 
1.9%
<p>The "Dark Eaters" has brought peace to the world by taking out the darkness that feeds on the human heart. One of the only 9 people left in the world with a special ability, Elaiza Ikeda, appears before a "dark-born" Yama, who gives people darkness...</p>1
 
1.9%
<p>Off and Boat have decided to go to an abandoned asylum. As the darkest secret of the asylum reveals, they encounter an accident that has never happened to any show before. </p>1
 
1.9%
<p>December 1941 marks the shift to a new chapter in the War Against Humanity. New fronts open up, exposing millions more to the horrors of war. Other developments continue their path of continuous escalation.</p>1
 
1.9%
<p>It's not Tuesday, but it's tacos! Tregaye Fraser wants to spend more time with her oldest son, so to get a little quality time with Treshawn, Tregaye makes Fish Tacos, Soy Pineapple Flank Steak Tacos, Roast Corn and a Mango Slaw.</p>1
 
1.9%
Other values (7)7
 
13.2%
(Missing)36
67.9%

Length

2022-09-05T21:41:54.982650image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the31
 
6.2%
to17
 
3.4%
and15
 
3.0%
a12
 
2.4%
with10
 
2.0%
of8
 
1.6%
p7
 
1.4%
in5
 
1.0%
her5
 
1.0%
up4
 
0.8%
Other values (319)387
77.2%

Most occurring characters

ValueCountFrequency (%)
480
15.5%
e283
 
9.1%
a211
 
6.8%
t197
 
6.3%
o155
 
5.0%
i151
 
4.9%
n151
 
4.9%
s150
 
4.8%
r148
 
4.8%
h127
 
4.1%
Other values (62)1053
33.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2266
73.0%
Space Separator487
 
15.7%
Uppercase Letter140
 
4.5%
Other Punctuation106
 
3.4%
Math Symbol88
 
2.8%
Decimal Number15
 
0.5%
Dash Punctuation4
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e283
12.5%
a211
 
9.3%
t197
 
8.7%
o155
 
6.8%
i151
 
6.7%
n151
 
6.7%
s150
 
6.6%
r148
 
6.5%
h127
 
5.6%
l86
 
3.8%
Other values (16)607
26.8%
Uppercase Letter
ValueCountFrequency (%)
T21
15.0%
S15
 
10.7%
A12
 
8.6%
C9
 
6.4%
F8
 
5.7%
Y7
 
5.0%
O7
 
5.0%
P7
 
5.0%
I6
 
4.3%
W5
 
3.6%
Other values (15)43
30.7%
Other Punctuation
ValueCountFrequency (%)
,27
25.5%
.26
24.5%
/23
21.7%
'11
10.4%
"6
 
5.7%
!4
 
3.8%
?3
 
2.8%
#3
 
2.8%
&1
 
0.9%
:1
 
0.9%
Decimal Number
ValueCountFrequency (%)
15
33.3%
04
26.7%
23
20.0%
92
 
13.3%
41
 
6.7%
Space Separator
ValueCountFrequency (%)
480
98.6%
 7
 
1.4%
Math Symbol
ValueCountFrequency (%)
<44
50.0%
>44
50.0%
Dash Punctuation
ValueCountFrequency (%)
-4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2406
77.5%
Common700
 
22.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e283
 
11.8%
a211
 
8.8%
t197
 
8.2%
o155
 
6.4%
i151
 
6.3%
n151
 
6.3%
s150
 
6.2%
r148
 
6.2%
h127
 
5.3%
l86
 
3.6%
Other values (41)747
31.0%
Common
ValueCountFrequency (%)
480
68.6%
<44
 
6.3%
>44
 
6.3%
,27
 
3.9%
.26
 
3.7%
/23
 
3.3%
'11
 
1.6%
 7
 
1.0%
"6
 
0.9%
15
 
0.7%
Other values (11)27
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII3099
99.8%
None7
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
480
15.5%
e283
 
9.1%
a211
 
6.8%
t197
 
6.4%
o155
 
5.0%
i151
 
4.9%
n151
 
4.9%
s150
 
4.8%
r148
 
4.8%
h127
 
4.1%
Other values (61)1046
33.8%
None
ValueCountFrequency (%)
 7
100.0%

rating.average
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct4
Distinct (%)100.0%
Missing49
Missing (%)92.5%
Memory size552.0 B
10.0
7.5
6.0
8.0

Length

Max length4
Median length3
Mean length3.25
Min length3

Characters and Unicode

Total characters13
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st row10.0
2nd row7.5
3rd row6.0
4th row8.0

Common Values

ValueCountFrequency (%)
10.01
 
1.9%
7.51
 
1.9%
6.01
 
1.9%
8.01
 
1.9%
(Missing)49
92.5%

Length

2022-09-05T21:41:55.076877image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:41:55.166414image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
10.01
25.0%
7.51
25.0%
6.01
25.0%
8.01
25.0%

Most occurring characters

ValueCountFrequency (%)
04
30.8%
.4
30.8%
11
 
7.7%
71
 
7.7%
51
 
7.7%
61
 
7.7%
81
 
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number9
69.2%
Other Punctuation4
30.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
04
44.4%
11
 
11.1%
71
 
11.1%
51
 
11.1%
61
 
11.1%
81
 
11.1%
Other Punctuation
ValueCountFrequency (%)
.4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common13
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
04
30.8%
.4
30.8%
11
 
7.7%
71
 
7.7%
51
 
7.7%
61
 
7.7%
81
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII13
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
04
30.8%
.4
30.8%
11
 
7.7%
71
 
7.7%
51
 
7.7%
61
 
7.7%
81
 
7.7%

_links.self.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct53
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size552.0 B
https://api.tvmaze.com/episodes/1988859
 
1
https://api.tvmaze.com/episodes/1986156
 
1
https://api.tvmaze.com/episodes/1986158
 
1
https://api.tvmaze.com/episodes/2000058
 
1
https://api.tvmaze.com/episodes/2000059
 
1
Other values (48)
48 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters2067
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique53 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/1988859
2nd rowhttps://api.tvmaze.com/episodes/1986140
3rd rowhttps://api.tvmaze.com/episodes/2386106
4th rowhttps://api.tvmaze.com/episodes/2138925
5th rowhttps://api.tvmaze.com/episodes/1962057

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19888591
 
1.9%
https://api.tvmaze.com/episodes/19861561
 
1.9%
https://api.tvmaze.com/episodes/19861581
 
1.9%
https://api.tvmaze.com/episodes/20000581
 
1.9%
https://api.tvmaze.com/episodes/20000591
 
1.9%
https://api.tvmaze.com/episodes/20399361
 
1.9%
https://api.tvmaze.com/episodes/21102461
 
1.9%
https://api.tvmaze.com/episodes/21817961
 
1.9%
https://api.tvmaze.com/episodes/22893211
 
1.9%
https://api.tvmaze.com/episodes/23181021
 
1.9%
Other values (43)43
81.1%

Length

2022-09-05T21:41:55.240826image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19888591
 
1.9%
https://api.tvmaze.com/episodes/19861401
 
1.9%
https://api.tvmaze.com/episodes/23861061
 
1.9%
https://api.tvmaze.com/episodes/21389251
 
1.9%
https://api.tvmaze.com/episodes/19620571
 
1.9%
https://api.tvmaze.com/episodes/19725651
 
1.9%
https://api.tvmaze.com/episodes/19725661
 
1.9%
https://api.tvmaze.com/episodes/19985781
 
1.9%
https://api.tvmaze.com/episodes/19985791
 
1.9%
https://api.tvmaze.com/episodes/21133201
 
1.9%
Other values (43)43
81.1%

Most occurring characters

ValueCountFrequency (%)
/212
 
10.3%
t159
 
7.7%
p159
 
7.7%
s159
 
7.7%
e159
 
7.7%
a106
 
5.1%
i106
 
5.1%
.106
 
5.1%
m106
 
5.1%
o106
 
5.1%
Other values (16)689
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1325
64.1%
Other Punctuation371
 
17.9%
Decimal Number371
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t159
12.0%
p159
12.0%
s159
12.0%
e159
12.0%
a106
8.0%
i106
8.0%
m106
8.0%
o106
8.0%
h53
 
4.0%
d53
 
4.0%
Other values (3)159
12.0%
Decimal Number
ValueCountFrequency (%)
166
17.8%
951
13.7%
251
13.7%
842
11.3%
034
9.2%
631
8.4%
731
8.4%
524
 
6.5%
323
 
6.2%
418
 
4.9%
Other Punctuation
ValueCountFrequency (%)
/212
57.1%
.106
28.6%
:53
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin1325
64.1%
Common742
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/212
28.6%
.106
14.3%
166
 
8.9%
:53
 
7.1%
951
 
6.9%
251
 
6.9%
842
 
5.7%
034
 
4.6%
631
 
4.2%
731
 
4.2%
Other values (3)65
 
8.8%
Latin
ValueCountFrequency (%)
t159
12.0%
p159
12.0%
s159
12.0%
e159
12.0%
a106
8.0%
i106
8.0%
m106
8.0%
o106
8.0%
h53
 
4.0%
d53
 
4.0%
Other values (3)159
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2067
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/212
 
10.3%
t159
 
7.7%
p159
 
7.7%
s159
 
7.7%
e159
 
7.7%
a106
 
5.1%
i106
 
5.1%
.106
 
5.1%
m106
 
5.1%
o106
 
5.1%
Other values (16)689
33.3%

_embedded.show.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct44
Distinct (%)83.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46702.45283
Minimum3734
Maximum62545
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size552.0 B
2022-09-05T21:41:55.332467image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum3734
5-th percentile11502
Q147912
median51125
Q353754
95-th percentile61398.6
Maximum62545
Range58811
Interquartile range (IQR)5842

Descriptive statistics

Standard deviation14368.10177
Coefficient of variation (CV)0.3076519733
Kurtosis2.473088658
Mean46702.45283
Median Absolute Deviation (MAD)2763
Skewness-1.764791745
Sum2475230
Variance206442348.5
MonotonicityNot monotonic
2022-09-05T21:41:55.442496image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
524514
 
7.5%
479122
 
3.8%
511252
 
3.8%
252942
 
3.8%
527822
 
3.8%
115022
 
3.8%
528062
 
3.8%
513141
 
1.9%
579451
 
1.9%
37341
 
1.9%
Other values (34)34
64.2%
ValueCountFrequency (%)
37341
1.9%
40911
1.9%
115022
3.8%
196671
1.9%
252942
3.8%
306061
1.9%
355511
1.9%
402321
1.9%
408681
1.9%
416481
1.9%
ValueCountFrequency (%)
625451
1.9%
617551
1.9%
615361
1.9%
613071
1.9%
608481
1.9%
588441
1.9%
579561
1.9%
579451
1.9%
566051
1.9%
559191
1.9%

_embedded.show.url
Categorical

HIGH CORRELATION
UNIFORM

Distinct44
Distinct (%)83.0%
Missing0
Missing (%)0.0%
Memory size552.0 B
https://www.tvmaze.com/shows/52451/the-burning-river
 
4
https://www.tvmaze.com/shows/47912/the-wolf
 
2
https://www.tvmaze.com/shows/51125/detention
 
2
https://www.tvmaze.com/shows/25294/ufc-fight-pass-prelims
 
2
https://www.tvmaze.com/shows/52782/mr-right-is-here
 
2
Other values (39)
41 

Length

Max length64
Median length57
Mean length50.8490566
Min length38

Characters and Unicode

Total characters2695
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)69.8%

Sample

1st rowhttps://www.tvmaze.com/shows/41648/sim-for-you
2nd rowhttps://www.tvmaze.com/shows/35551/soul-land
3rd rowhttps://www.tvmaze.com/shows/49206/xian-feng-jian-yu-lu
4th rowhttps://www.tvmaze.com/shows/49740/tokyo-joshi-pro-wrestling
5th rowhttps://www.tvmaze.com/shows/51670/heaven-officials-blessing

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/shows/52451/the-burning-river4
 
7.5%
https://www.tvmaze.com/shows/47912/the-wolf2
 
3.8%
https://www.tvmaze.com/shows/51125/detention2
 
3.8%
https://www.tvmaze.com/shows/25294/ufc-fight-pass-prelims2
 
3.8%
https://www.tvmaze.com/shows/52782/mr-right-is-here2
 
3.8%
https://www.tvmaze.com/shows/11502/hver-gang-vi-motes2
 
3.8%
https://www.tvmaze.com/shows/52806/ultimate-note2
 
3.8%
https://www.tvmaze.com/shows/51314/maskorama1
 
1.9%
https://www.tvmaze.com/shows/57945/i-like-to-watch1
 
1.9%
https://www.tvmaze.com/shows/3734/the-streamy-awards1
 
1.9%
Other values (34)34
64.2%

Length

2022-09-05T21:41:55.545467image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/shows/52451/the-burning-river4
 
7.5%
https://www.tvmaze.com/shows/51125/detention2
 
3.8%
https://www.tvmaze.com/shows/25294/ufc-fight-pass-prelims2
 
3.8%
https://www.tvmaze.com/shows/52782/mr-right-is-here2
 
3.8%
https://www.tvmaze.com/shows/11502/hver-gang-vi-motes2
 
3.8%
https://www.tvmaze.com/shows/52806/ultimate-note2
 
3.8%
https://www.tvmaze.com/shows/47912/the-wolf2
 
3.8%
https://www.tvmaze.com/shows/57956/hjem-til-jul1
 
1.9%
https://www.tvmaze.com/shows/49206/xian-feng-jian-yu-lu1
 
1.9%
https://www.tvmaze.com/shows/49740/tokyo-joshi-pro-wrestling1
 
1.9%
Other values (34)34
64.2%

Most occurring characters

ValueCountFrequency (%)
/265
 
9.8%
w233
 
8.6%
t212
 
7.9%
s207
 
7.7%
o155
 
5.8%
h137
 
5.1%
e137
 
5.1%
m131
 
4.9%
.106
 
3.9%
a105
 
3.9%
Other values (30)1007
37.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1903
70.6%
Other Punctuation424
 
15.7%
Decimal Number268
 
9.9%
Dash Punctuation100
 
3.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w233
12.2%
t212
11.1%
s207
10.9%
o155
 
8.1%
h137
 
7.2%
e137
 
7.2%
m131
 
6.9%
a105
 
5.5%
v68
 
3.6%
c68
 
3.6%
Other values (16)450
23.6%
Decimal Number
ValueCountFrequency (%)
556
20.9%
232
11.9%
431
11.6%
130
11.2%
024
9.0%
823
8.6%
621
 
7.8%
920
 
7.5%
716
 
6.0%
315
 
5.6%
Other Punctuation
ValueCountFrequency (%)
/265
62.5%
.106
 
25.0%
:53
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-100
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1903
70.6%
Common792
29.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
w233
12.2%
t212
11.1%
s207
10.9%
o155
 
8.1%
h137
 
7.2%
e137
 
7.2%
m131
 
6.9%
a105
 
5.5%
v68
 
3.6%
c68
 
3.6%
Other values (16)450
23.6%
Common
ValueCountFrequency (%)
/265
33.5%
.106
 
13.4%
-100
 
12.6%
556
 
7.1%
:53
 
6.7%
232
 
4.0%
431
 
3.9%
130
 
3.8%
024
 
3.0%
823
 
2.9%
Other values (4)72
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII2695
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/265
 
9.8%
w233
 
8.6%
t212
 
7.9%
s207
 
7.7%
o155
 
5.8%
h137
 
5.1%
e137
 
5.1%
m131
 
4.9%
.106
 
3.9%
a105
 
3.9%
Other values (30)1007
37.4%

_embedded.show.name
Categorical

HIGH CORRELATION
UNIFORM

Distinct44
Distinct (%)83.0%
Missing0
Missing (%)0.0%
Memory size552.0 B
The Burning River
 
4
The Wolf
 
2
Detention
 
2
UFC Fight Pass Prelims
 
2
Mr. Right is Here!
 
2
Other values (39)
41 

Length

Max length31
Median length25
Mean length16.11320755
Min length4

Characters and Unicode

Total characters854
Distinct characters66
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)69.8%

Sample

1st rowSim for You
2nd rowSoul Land
3rd rowXian Feng Jian Yu Lu
4th rowTokyo Joshi Pro Wrestling
5th rowHeaven Official's Blessing

Common Values

ValueCountFrequency (%)
The Burning River4
 
7.5%
The Wolf2
 
3.8%
Detention2
 
3.8%
UFC Fight Pass Prelims2
 
3.8%
Mr. Right is Here!2
 
3.8%
Hver gang vi møtes2
 
3.8%
Ultimate Note2
 
3.8%
Maskorama1
 
1.9%
I Like to Watch1
 
1.9%
The Streamy Awards1
 
1.9%
Other values (34)34
64.2%

Length

2022-09-05T21:41:55.645499image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the10
 
6.5%
river4
 
2.6%
burning4
 
2.6%
gang2
 
1.3%
lovely2
 
1.3%
by2
 
1.3%
gods2
 
1.3%
war2
 
1.3%
no2
 
1.3%
week2
 
1.3%
Other values (105)121
79.1%

Most occurring characters

ValueCountFrequency (%)
100
 
11.7%
e80
 
9.4%
i57
 
6.7%
a47
 
5.5%
r46
 
5.4%
n44
 
5.2%
o41
 
4.8%
t38
 
4.4%
s37
 
4.3%
l25
 
2.9%
Other values (56)339
39.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter594
69.6%
Uppercase Letter143
 
16.7%
Space Separator100
 
11.7%
Other Punctuation12
 
1.4%
Decimal Number5
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e80
13.5%
i57
 
9.6%
a47
 
7.9%
r46
 
7.7%
n44
 
7.4%
o41
 
6.9%
t38
 
6.4%
s37
 
6.2%
l25
 
4.2%
h23
 
3.9%
Other values (24)156
26.3%
Uppercase Letter
ValueCountFrequency (%)
W17
 
11.9%
T14
 
9.8%
B12
 
8.4%
S11
 
7.7%
R10
 
7.0%
H8
 
5.6%
C7
 
4.9%
L6
 
4.2%
P6
 
4.2%
F6
 
4.2%
Other values (14)46
32.2%
Other Punctuation
ValueCountFrequency (%)
'4
33.3%
:3
25.0%
!2
16.7%
.2
16.7%
?1
 
8.3%
Decimal Number
ValueCountFrequency (%)
23
60.0%
02
40.0%
Space Separator
ValueCountFrequency (%)
100
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin730
85.5%
Common117
 
13.7%
Cyrillic7
 
0.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e80
 
11.0%
i57
 
7.8%
a47
 
6.4%
r46
 
6.3%
n44
 
6.0%
o41
 
5.6%
t38
 
5.2%
s37
 
5.1%
l25
 
3.4%
h23
 
3.2%
Other values (41)292
40.0%
Common
ValueCountFrequency (%)
100
85.5%
'4
 
3.4%
:3
 
2.6%
23
 
2.6%
02
 
1.7%
!2
 
1.7%
.2
 
1.7%
?1
 
0.9%
Cyrillic
ValueCountFrequency (%)
З1
14.3%
о1
14.3%
м1
14.3%
б1
14.3%
е1
14.3%
т1
14.3%
ы1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII843
98.7%
Cyrillic7
 
0.8%
None4
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
100
 
11.9%
e80
 
9.5%
i57
 
6.8%
a47
 
5.6%
r46
 
5.5%
n44
 
5.2%
o41
 
4.9%
t38
 
4.5%
s37
 
4.4%
l25
 
3.0%
Other values (47)328
38.9%
None
ValueCountFrequency (%)
ø3
75.0%
å1
 
25.0%
Cyrillic
ValueCountFrequency (%)
З1
14.3%
о1
14.3%
м1
14.3%
б1
14.3%
е1
14.3%
т1
14.3%
ы1
14.3%

_embedded.show.type
Categorical

HIGH CORRELATION

Distinct9
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Memory size552.0 B
Scripted
23 
Reality
Animation
Sports
Documentary
Other values (4)

Length

Max length11
Median length10
Mean length8.150943396
Min length6

Characters and Unicode

Total characters432
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)3.8%

Sample

1st rowReality
2nd rowAnimation
3rd rowAnimation
4th rowSports
5th rowAnimation

Common Values

ValueCountFrequency (%)
Scripted23
43.4%
Reality7
 
13.2%
Animation7
 
13.2%
Sports5
 
9.4%
Documentary4
 
7.5%
Talk Show3
 
5.7%
Game Show2
 
3.8%
Variety1
 
1.9%
Award Show1
 
1.9%

Length

2022-09-05T21:41:55.733640image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:41:55.831255image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
scripted23
39.0%
reality7
 
11.9%
animation7
 
11.9%
show6
 
10.2%
sports5
 
8.5%
documentary4
 
6.8%
talk3
 
5.1%
game2
 
3.4%
variety1
 
1.7%
award1
 
1.7%

Most occurring characters

ValueCountFrequency (%)
t47
10.9%
i45
10.4%
e37
 
8.6%
S34
 
7.9%
r34
 
7.9%
p28
 
6.5%
c27
 
6.2%
a25
 
5.8%
d24
 
5.6%
o22
 
5.1%
Other values (16)109
25.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter367
85.0%
Uppercase Letter59
 
13.7%
Space Separator6
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t47
12.8%
i45
12.3%
e37
10.1%
r34
9.3%
p28
7.6%
c27
7.4%
a25
6.8%
d24
 
6.5%
o22
 
6.0%
n18
 
4.9%
Other values (8)60
16.3%
Uppercase Letter
ValueCountFrequency (%)
S34
57.6%
A8
 
13.6%
R7
 
11.9%
D4
 
6.8%
T3
 
5.1%
G2
 
3.4%
V1
 
1.7%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin426
98.6%
Common6
 
1.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t47
11.0%
i45
10.6%
e37
 
8.7%
S34
 
8.0%
r34
 
8.0%
p28
 
6.6%
c27
 
6.3%
a25
 
5.9%
d24
 
5.6%
o22
 
5.2%
Other values (15)103
24.2%
Common
ValueCountFrequency (%)
6
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII432
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t47
10.9%
i45
10.4%
e37
 
8.6%
S34
 
7.9%
r34
 
7.9%
p28
 
6.5%
c27
 
6.2%
a25
 
5.8%
d24
 
5.6%
o22
 
5.1%
Other values (16)109
25.2%

_embedded.show.language
Categorical

HIGH CORRELATION

Distinct9
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Memory size552.0 B
English
18 
Chinese
15 
Norwegian
Japanese
Korean
Other values (4)

Length

Max length9
Median length7
Mean length7.056603774
Min length4

Characters and Unicode

Total characters374
Distinct characters25
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)5.7%

Sample

1st rowKorean
2nd rowChinese
3rd rowChinese
4th rowJapanese
5th rowChinese

Common Values

ValueCountFrequency (%)
English18
34.0%
Chinese15
28.3%
Norwegian7
 
13.2%
Japanese4
 
7.5%
Korean3
 
5.7%
Thai3
 
5.7%
Russian1
 
1.9%
Dutch1
 
1.9%
Arabic1
 
1.9%

Length

2022-09-05T21:41:55.922358image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:41:56.026131image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
english18
34.0%
chinese15
28.3%
norwegian7
 
13.2%
japanese4
 
7.5%
korean3
 
5.7%
thai3
 
5.7%
russian1
 
1.9%
dutch1
 
1.9%
arabic1
 
1.9%

Most occurring characters

ValueCountFrequency (%)
n48
12.8%
e48
12.8%
i45
12.0%
s39
10.4%
h37
9.9%
g25
6.7%
a23
 
6.1%
E18
 
4.8%
l18
 
4.8%
C15
 
4.0%
Other values (15)58
15.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter321
85.8%
Uppercase Letter53
 
14.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n48
15.0%
e48
15.0%
i45
14.0%
s39
12.1%
h37
11.5%
g25
7.8%
a23
7.2%
l18
 
5.6%
r11
 
3.4%
o10
 
3.1%
Other values (6)17
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
E18
34.0%
C15
28.3%
N7
 
13.2%
J4
 
7.5%
K3
 
5.7%
T3
 
5.7%
R1
 
1.9%
D1
 
1.9%
A1
 
1.9%

Most occurring scripts

ValueCountFrequency (%)
Latin374
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n48
12.8%
e48
12.8%
i45
12.0%
s39
10.4%
h37
9.9%
g25
6.7%
a23
 
6.1%
E18
 
4.8%
l18
 
4.8%
C15
 
4.0%
Other values (15)58
15.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII374
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n48
12.8%
e48
12.8%
i45
12.0%
s39
10.4%
h37
9.9%
g25
6.7%
a23
 
6.1%
E18
 
4.8%
l18
 
4.8%
C15
 
4.0%
Other values (15)58
15.5%

_embedded.show.genres
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size552.0 B

_embedded.show.status
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size552.0 B
Running
29 
Ended
21 
To Be Determined

Length

Max length16
Median length7
Mean length6.716981132
Min length5

Characters and Unicode

Total characters356
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRunning
2nd rowRunning
3rd rowRunning
4th rowRunning
5th rowRunning

Common Values

ValueCountFrequency (%)
Running29
54.7%
Ended21
39.6%
To Be Determined3
 
5.7%

Length

2022-09-05T21:41:56.134925image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:41:56.225340image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
running29
49.2%
ended21
35.6%
to3
 
5.1%
be3
 
5.1%
determined3
 
5.1%

Most occurring characters

ValueCountFrequency (%)
n111
31.2%
d45
12.6%
e33
 
9.3%
i32
 
9.0%
R29
 
8.1%
u29
 
8.1%
g29
 
8.1%
E21
 
5.9%
6
 
1.7%
T3
 
0.8%
Other values (6)18
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter291
81.7%
Uppercase Letter59
 
16.6%
Space Separator6
 
1.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n111
38.1%
d45
15.5%
e33
 
11.3%
i32
 
11.0%
u29
 
10.0%
g29
 
10.0%
o3
 
1.0%
t3
 
1.0%
r3
 
1.0%
m3
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
R29
49.2%
E21
35.6%
T3
 
5.1%
B3
 
5.1%
D3
 
5.1%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin350
98.3%
Common6
 
1.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
n111
31.7%
d45
12.9%
e33
 
9.4%
i32
 
9.1%
R29
 
8.3%
u29
 
8.3%
g29
 
8.3%
E21
 
6.0%
T3
 
0.9%
o3
 
0.9%
Other values (5)15
 
4.3%
Common
ValueCountFrequency (%)
6
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII356
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n111
31.2%
d45
12.6%
e33
 
9.3%
i32
 
9.0%
R29
 
8.1%
u29
 
8.1%
g29
 
8.1%
E21
 
5.9%
6
 
1.7%
T3
 
0.8%
Other values (6)18
 
5.1%

_embedded.show.runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct15
Distinct (%)38.5%
Missing14
Missing (%)26.4%
Infinite0
Infinite (%)0.0%
Mean42.58974359
Minimum5
Maximum180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size552.0 B
2022-09-05T21:41:56.293794image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile9.8
Q120
median30
Q345
95-th percentile120
Maximum180
Range175
Interquartile range (IQR)25

Descriptive statistics

Standard deviation35.60877919
Coefficient of variation (CV)0.8360881326
Kurtosis5.337066618
Mean42.58974359
Median Absolute Deviation (MAD)15
Skewness2.105722461
Sum1661
Variance1267.985155
MonotonicityNot monotonic
2022-09-05T21:41:56.375113image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
4511
20.8%
155
 
9.4%
203
 
5.7%
253
 
5.7%
303
 
5.7%
603
 
5.7%
1202
 
3.8%
902
 
3.8%
161
 
1.9%
81
 
1.9%
Other values (5)5
 
9.4%
(Missing)14
26.4%
ValueCountFrequency (%)
51
 
1.9%
81
 
1.9%
101
 
1.9%
155
9.4%
161
 
1.9%
203
5.7%
231
 
1.9%
241
 
1.9%
253
5.7%
303
5.7%
ValueCountFrequency (%)
1801
 
1.9%
1202
 
3.8%
902
 
3.8%
603
 
5.7%
4511
20.8%
303
 
5.7%
253
 
5.7%
241
 
1.9%
231
 
1.9%
203
 
5.7%

_embedded.show.averageRuntime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct29
Distinct (%)60.4%
Missing5
Missing (%)9.4%
Infinite0
Infinite (%)0.0%
Mean42.25
Minimum5
Maximum180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size552.0 B
2022-09-05T21:41:56.468615image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile9.7
Q119.5
median36.5
Q351
95-th percentile115.8
Maximum180
Range175
Interquartile range (IQR)31.5

Descriptive statistics

Standard deviation34.26585671
Coefficient of variation (CV)0.8110261944
Kurtosis5.044379514
Mean42.25
Median Absolute Deviation (MAD)16.5
Skewness1.989605841
Sum2028
Variance1174.148936
MonotonicityNot monotonic
2022-09-05T21:41:56.561545image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
4510
18.9%
253
 
5.7%
742
 
3.8%
1202
 
3.8%
112
 
3.8%
172
 
3.8%
542
 
3.8%
512
 
3.8%
302
 
3.8%
202
 
3.8%
Other values (19)19
35.8%
(Missing)5
 
9.4%
ValueCountFrequency (%)
51
1.9%
71
1.9%
91
1.9%
112
3.8%
121
1.9%
131
1.9%
151
1.9%
161
1.9%
172
3.8%
181
1.9%
ValueCountFrequency (%)
1801
 
1.9%
1202
 
3.8%
1081
 
1.9%
881
 
1.9%
742
 
3.8%
601
 
1.9%
561
 
1.9%
542
 
3.8%
512
 
3.8%
4510
18.9%

_embedded.show.premiered
Categorical

HIGH CORRELATION

Distinct39
Distinct (%)73.6%
Missing0
Missing (%)0.0%
Memory size552.0 B
2020-12-11
2020-12-10
2020-12-05
 
3
2020-11-14
 
2
2020-11-19
 
2
Other values (34)
38 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters530
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)56.6%

Sample

1st row2019-03-25
2nd row2018-01-13
3rd row2020-07-11
4th row2013-01-30
5th row2020-10-31

Common Values

ValueCountFrequency (%)
2020-12-114
 
7.5%
2020-12-104
 
7.5%
2020-12-053
 
5.7%
2020-11-142
 
3.8%
2020-11-192
 
3.8%
2017-01-152
 
3.8%
2020-11-072
 
3.8%
2012-01-282
 
3.8%
2020-10-032
 
3.8%
2020-09-051
 
1.9%
Other values (29)29
54.7%

Length

2022-09-05T21:41:56.645378image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-114
 
7.5%
2020-12-104
 
7.5%
2020-12-053
 
5.7%
2020-11-142
 
3.8%
2020-11-192
 
3.8%
2017-01-152
 
3.8%
2020-11-072
 
3.8%
2012-01-282
 
3.8%
2020-10-032
 
3.8%
2020-12-031
 
1.9%
Other values (29)29
54.7%

Most occurring characters

ValueCountFrequency (%)
0141
26.6%
2113
21.3%
-106
20.0%
1101
19.1%
919
 
3.6%
313
 
2.5%
711
 
2.1%
88
 
1.5%
57
 
1.3%
47
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number424
80.0%
Dash Punctuation106
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0141
33.3%
2113
26.7%
1101
23.8%
919
 
4.5%
313
 
3.1%
711
 
2.6%
88
 
1.9%
57
 
1.7%
47
 
1.7%
64
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
-106
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common530
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0141
26.6%
2113
21.3%
-106
20.0%
1101
19.1%
919
 
3.6%
313
 
2.5%
711
 
2.1%
88
 
1.5%
57
 
1.3%
47
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII530
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0141
26.6%
2113
21.3%
-106
20.0%
1101
19.1%
919
 
3.6%
313
 
2.5%
711
 
2.1%
88
 
1.5%
57
 
1.3%
47
 
1.3%

_embedded.show.ended
Categorical

HIGH CORRELATION
MISSING

Distinct10
Distinct (%)47.6%
Missing32
Missing (%)60.4%
Memory size552.0 B
2021-01-01
2021-01-02
2020-12-19
2021-01-04
2020-12-18
Other values (5)

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters210
Distinct characters8
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)14.3%

Sample

1st row2021-01-04
2nd row2021-01-04
3rd row2020-12-18
4th row2020-12-18
5th row2020-12-24

Common Values

ValueCountFrequency (%)
2021-01-014
 
7.5%
2021-01-023
 
5.7%
2020-12-193
 
5.7%
2021-01-042
 
3.8%
2020-12-182
 
3.8%
2020-12-262
 
3.8%
2021-01-092
 
3.8%
2020-12-241
 
1.9%
2020-12-121
 
1.9%
2021-08-211
 
1.9%
(Missing)32
60.4%

Length

2022-09-05T21:41:56.725814image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:41:56.838625image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
2021-01-014
19.0%
2021-01-023
14.3%
2020-12-193
14.3%
2021-01-042
9.5%
2020-12-182
9.5%
2020-12-262
9.5%
2021-01-092
9.5%
2020-12-241
 
4.8%
2020-12-121
 
4.8%
2021-08-211
 
4.8%

Most occurring characters

ValueCountFrequency (%)
259
28.1%
053
25.2%
143
20.5%
-42
20.0%
95
 
2.4%
43
 
1.4%
83
 
1.4%
62
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number168
80.0%
Dash Punctuation42
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
259
35.1%
053
31.5%
143
25.6%
95
 
3.0%
43
 
1.8%
83
 
1.8%
62
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
-42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common210
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
259
28.1%
053
25.2%
143
20.5%
-42
20.0%
95
 
2.4%
43
 
1.4%
83
 
1.4%
62
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII210
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
259
28.1%
053
25.2%
143
20.5%
-42
20.0%
95
 
2.4%
43
 
1.4%
83
 
1.4%
62
 
1.0%

_embedded.show.officialSite
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct40
Distinct (%)83.3%
Missing5
Missing (%)9.4%
Memory size552.0 B
https://v.youku.com/v_show/id_XNDk1MzY2NzgwNA==.html?spm=a2h0c.8166622.PhoneSokuProgram_1.dtitle&s=aaed627feea749d7a99d
https://www.netflix.com/title/81329144
 
2
https://www.iqiyi.com/lib/m_213579814.html
 
2
https://www.ufc.tv/page/fightpass
 
2
https://play.tv2.no/programmer/underholdning/hver-gang-vi-moetes
 
2
Other values (35)
36 

Length

Max length119
Median length63
Mean length52.75
Min length23

Characters and Unicode

Total characters2532
Distinct characters70
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)70.8%

Sample

1st rowhttps://www.vlive.tv/video/121637
2nd rowhttps://v.qq.com/detail/m/m441e3rjq9kwpsc.html
3rd rowhttps://v.qq.com/detail/m/mzc00200hc38s5x.html
4th rowhttps://www.ddtpro.com/
5th rowhttps://www.bilibili.com/tgcf

Common Values

ValueCountFrequency (%)
https://v.youku.com/v_show/id_XNDk1MzY2NzgwNA==.html?spm=a2h0c.8166622.PhoneSokuProgram_1.dtitle&s=aaed627feea749d7a99d4
 
7.5%
https://www.netflix.com/title/813291442
 
3.8%
https://www.iqiyi.com/lib/m_213579814.html2
 
3.8%
https://www.ufc.tv/page/fightpass2
 
3.8%
https://play.tv2.no/programmer/underholdning/hver-gang-vi-moetes2
 
3.8%
https://www.iqiyi.com/a_nvzsmw0tgx.html2
 
3.8%
https://www.tv-tokyo.co.jp/anoyume/intro/1
 
1.9%
http://www.streamys.org1
 
1.9%
https://www.amazon.com/Paranormal-Nightmare/dp/B07YLZPXT71
 
1.9%
https://www.youtube.com/playlist?list=PLvahqwMqN4M2o2ZzY6Y8a626Lf286LdVl1
 
1.9%
Other values (30)30
56.6%
(Missing)5
 
9.4%

Length

2022-09-05T21:41:56.961773image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://v.youku.com/v_show/id_xndk1mzy2nzgwna==.html?spm=a2h0c.8166622.phonesokuprogram_1.dtitle&s=aaed627feea749d7a99d4
 
8.3%
https://www.iqiyi.com/lib/m_213579814.html2
 
4.2%
https://www.ufc.tv/page/fightpass2
 
4.2%
https://play.tv2.no/programmer/underholdning/hver-gang-vi-moetes2
 
4.2%
https://www.iqiyi.com/a_nvzsmw0tgx.html2
 
4.2%
https://www.netflix.com/title/813291442
 
4.2%
https://play.tv2.no/nyheter/hjem-til-jul1
 
2.1%
https://v.qq.com/detail/m/mzc00200hc38s5x.html1
 
2.1%
https://www.ddtpro.com1
 
2.1%
https://www.bilibili.com/tgcf1
 
2.1%
Other values (30)30
62.5%

Most occurring characters

ValueCountFrequency (%)
t191
 
7.5%
/191
 
7.5%
s127
 
5.0%
e121
 
4.8%
o116
 
4.6%
.115
 
4.5%
w106
 
4.2%
h103
 
4.1%
a97
 
3.8%
i85
 
3.4%
Other values (60)1280
50.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1721
68.0%
Other Punctuation376
 
14.8%
Decimal Number227
 
9.0%
Uppercase Letter135
 
5.3%
Dash Punctuation31
 
1.2%
Math Symbol24
 
0.9%
Connector Punctuation18
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t191
 
11.1%
s127
 
7.4%
e121
 
7.0%
o116
 
6.7%
w106
 
6.2%
h103
 
6.0%
a97
 
5.6%
i85
 
4.9%
p84
 
4.9%
m81
 
4.7%
Other values (16)610
35.4%
Uppercase Letter
ValueCountFrequency (%)
N16
 
11.9%
P15
 
11.1%
A10
 
7.4%
Y10
 
7.4%
D9
 
6.7%
X8
 
5.9%
C7
 
5.2%
M6
 
4.4%
L6
 
4.4%
K5
 
3.7%
Other values (15)43
31.9%
Decimal Number
ValueCountFrequency (%)
240
17.6%
128
12.3%
626
11.5%
026
11.5%
424
10.6%
720
8.8%
920
8.8%
818
7.9%
315
 
6.6%
510
 
4.4%
Other Punctuation
ValueCountFrequency (%)
/191
50.8%
.115
30.6%
:48
 
12.8%
?9
 
2.4%
&7
 
1.9%
%6
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
-31
100.0%
Math Symbol
ValueCountFrequency (%)
=24
100.0%
Connector Punctuation
ValueCountFrequency (%)
_18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1856
73.3%
Common676
 
26.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
t191
 
10.3%
s127
 
6.8%
e121
 
6.5%
o116
 
6.2%
w106
 
5.7%
h103
 
5.5%
a97
 
5.2%
i85
 
4.6%
p84
 
4.5%
m81
 
4.4%
Other values (41)745
40.1%
Common
ValueCountFrequency (%)
/191
28.3%
.115
17.0%
:48
 
7.1%
240
 
5.9%
-31
 
4.6%
128
 
4.1%
626
 
3.8%
026
 
3.8%
424
 
3.6%
=24
 
3.6%
Other values (9)123
18.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII2532
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t191
 
7.5%
/191
 
7.5%
s127
 
5.0%
e121
 
4.8%
o116
 
4.6%
.115
 
4.5%
w106
 
4.2%
h103
 
4.1%
a97
 
3.8%
i85
 
3.4%
Other values (60)1280
50.6%

_embedded.show.schedule.time
Categorical

HIGH CORRELATION

Distinct12
Distinct (%)22.6%
Missing0
Missing (%)0.0%
Memory size552.0 B
35 
18:00
10:00
 
2
12:00
 
2
21:00
 
2
Other values (7)

Length

Max length5
Median length0
Mean length1.698113208
Min length0

Characters and Unicode

Total characters90
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)13.2%

Sample

1st row
2nd row10:00
3rd row10:00
4th row12:00
5th row11:00

Common Values

ValueCountFrequency (%)
35
66.0%
18:005
 
9.4%
10:002
 
3.8%
12:002
 
3.8%
21:002
 
3.8%
11:001
 
1.9%
06:001
 
1.9%
17:001
 
1.9%
00:001
 
1.9%
00:151
 
1.9%
Other values (2)2
 
3.8%

Length

2022-09-05T21:41:57.061130image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
18:005
27.8%
10:002
 
11.1%
12:002
 
11.1%
21:002
 
11.1%
11:001
 
5.6%
06:001
 
5.6%
17:001
 
5.6%
00:001
 
5.6%
00:151
 
5.6%
19:501
 
5.6%

Most occurring characters

ValueCountFrequency (%)
040
44.4%
:18
20.0%
117
18.9%
85
 
5.6%
24
 
4.4%
62
 
2.2%
52
 
2.2%
71
 
1.1%
91
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number72
80.0%
Other Punctuation18
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
040
55.6%
117
23.6%
85
 
6.9%
24
 
5.6%
62
 
2.8%
52
 
2.8%
71
 
1.4%
91
 
1.4%
Other Punctuation
ValueCountFrequency (%)
:18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common90
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
040
44.4%
:18
20.0%
117
18.9%
85
 
5.6%
24
 
4.4%
62
 
2.2%
52
 
2.2%
71
 
1.1%
91
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII90
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
040
44.4%
:18
20.0%
117
18.9%
85
 
5.6%
24
 
4.4%
62
 
2.2%
52
 
2.2%
71
 
1.1%
91
 
1.1%

_embedded.show.schedule.days
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size552.0 B

_embedded.show.rating.average
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct3
Distinct (%)75.0%
Missing49
Missing (%)92.5%
Memory size552.0 B
7.7
7.3
5.0

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters12
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)50.0%

Sample

1st row7.7
2nd row7.3
3rd row7.7
4th row5.0

Common Values

ValueCountFrequency (%)
7.72
 
3.8%
7.31
 
1.9%
5.01
 
1.9%
(Missing)49
92.5%

Length

2022-09-05T21:41:57.146766image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:41:57.236490image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
7.72
50.0%
7.31
25.0%
5.01
25.0%

Most occurring characters

ValueCountFrequency (%)
75
41.7%
.4
33.3%
31
 
8.3%
51
 
8.3%
01
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number8
66.7%
Other Punctuation4
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
75
62.5%
31
 
12.5%
51
 
12.5%
01
 
12.5%
Other Punctuation
ValueCountFrequency (%)
.4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common12
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
75
41.7%
.4
33.3%
31
 
8.3%
51
 
8.3%
01
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII12
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
75
41.7%
.4
33.3%
31
 
8.3%
51
 
8.3%
01
 
8.3%

_embedded.show.weight
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct36
Distinct (%)67.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.0754717
Minimum1
Maximum92
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size552.0 B
2022-09-05T21:41:57.319427image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.2
Q119
median30
Q345
95-th percentile82.6
Maximum92
Range91
Interquartile range (IQR)26

Descriptive statistics

Standard deviation23.12578403
Coefficient of variation (CV)0.6786636508
Kurtosis0.3827038507
Mean34.0754717
Median Absolute Deviation (MAD)14
Skewness0.8109809062
Sum1806
Variance534.8018868
MonotonicityNot monotonic
2022-09-05T21:41:57.418257image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
245
 
9.4%
443
 
5.7%
292
 
3.8%
192
 
3.8%
392
 
3.8%
12
 
3.8%
302
 
3.8%
452
 
3.8%
272
 
3.8%
42
 
3.8%
Other values (26)29
54.7%
ValueCountFrequency (%)
12
3.8%
21
1.9%
42
3.8%
61
1.9%
71
1.9%
81
1.9%
91
1.9%
111
1.9%
142
3.8%
192
3.8%
ValueCountFrequency (%)
921
1.9%
911
1.9%
881
1.9%
791
1.9%
741
1.9%
651
1.9%
631
1.9%
621
1.9%
521
1.9%
481
1.9%

_embedded.show.network
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing53
Missing (%)100.0%
Memory size552.0 B

_embedded.show.webChannel.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct26
Distinct (%)52.0%
Missing3
Missing (%)5.7%
Infinite0
Infinite (%)0.0%
Mean137.3
Minimum1
Maximum533
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size552.0 B
2022-09-05T21:41:57.511763image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.4
Q121
median104
Q3235.5
95-th percentile412.95
Maximum533
Range532
Interquartile range (IQR)214.5

Descriptive statistics

Standard deviation140.230459
Coefficient of variation (CV)1.021343474
Kurtosis0.3862348224
Mean137.3
Median Absolute Deviation (MAD)83
Skewness1.172979788
Sum6865
Variance19664.58163
MonotonicityNot monotonic
2022-09-05T21:41:57.612332image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
219
17.0%
1188
15.1%
2384
 
7.5%
453
 
5.7%
202
 
3.8%
672
 
3.8%
12
 
3.8%
1042
 
3.8%
3671
 
1.9%
3421
 
1.9%
Other values (16)16
30.2%
(Missing)3
 
5.7%
ValueCountFrequency (%)
12
 
3.8%
31
 
1.9%
151
 
1.9%
202
 
3.8%
219
17.0%
301
 
1.9%
321
 
1.9%
453
 
5.7%
511
 
1.9%
672
 
3.8%
ValueCountFrequency (%)
5331
 
1.9%
4521
 
1.9%
4171
 
1.9%
4081
 
1.9%
3791
 
1.9%
3671
 
1.9%
3421
 
1.9%
3271
 
1.9%
2941
 
1.9%
2384
7.5%

_embedded.show.webChannel.name
Categorical

HIGH CORRELATION
MISSING

Distinct26
Distinct (%)52.0%
Missing3
Missing (%)5.7%
Memory size552.0 B
YouTube
Youku
NRK TV
UFC Fight Pass
Crunchyroll
 
2
Other values (21)
24 

Length

Max length23
Median length13
Mean length8.14
Min length4

Characters and Unicode

Total characters407
Distinct characters47
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)36.0%

Sample

1st rowV LIVE
2nd rowTencent QQ
3rd rowTencent QQ
4th rowDDTUniverse
5th rowBilibili

Common Values

ValueCountFrequency (%)
YouTube9
17.0%
Youku8
15.1%
NRK TV4
 
7.5%
UFC Fight Pass3
 
5.7%
Crunchyroll2
 
3.8%
iQIYI2
 
3.8%
Netflix2
 
3.8%
Tencent QQ2
 
3.8%
WeTV1
 
1.9%
Paravi1
 
1.9%
Other values (16)16
30.2%
(Missing)3
 
5.7%

Length

2022-09-05T21:41:57.715371image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
youtube9
 
12.5%
tv8
 
11.1%
youku8
 
11.1%
nrk4
 
5.6%
ufc3
 
4.2%
fight3
 
4.2%
pass3
 
4.2%
netflix2
 
2.8%
tencent2
 
2.8%
qq2
 
2.8%
Other values (26)28
38.9%

Most occurring characters

ValueCountFrequency (%)
u38
 
9.3%
e33
 
8.1%
o27
 
6.6%
T24
 
5.9%
22
 
5.4%
Y19
 
4.7%
i19
 
4.7%
t14
 
3.4%
r13
 
3.2%
V13
 
3.2%
Other values (37)185
45.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter253
62.2%
Uppercase Letter129
31.7%
Space Separator22
 
5.4%
Math Symbol1
 
0.2%
Decimal Number1
 
0.2%
Other Punctuation1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u38
15.0%
e33
13.0%
o27
10.7%
i19
 
7.5%
t14
 
5.5%
r13
 
5.1%
l12
 
4.7%
s11
 
4.3%
a11
 
4.3%
n11
 
4.3%
Other values (14)64
25.3%
Uppercase Letter
ValueCountFrequency (%)
T24
18.6%
Y19
14.7%
V13
10.1%
N9
 
7.0%
C7
 
5.4%
I7
 
5.4%
F6
 
4.7%
P6
 
4.7%
Q6
 
4.7%
K5
 
3.9%
Other values (9)27
20.9%
Space Separator
ValueCountFrequency (%)
22
100.0%
Math Symbol
ValueCountFrequency (%)
+1
100.0%
Decimal Number
ValueCountFrequency (%)
21
100.0%
Other Punctuation
ValueCountFrequency (%)
.1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin382
93.9%
Common25
 
6.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
u38
 
9.9%
e33
 
8.6%
o27
 
7.1%
T24
 
6.3%
Y19
 
5.0%
i19
 
5.0%
t14
 
3.7%
r13
 
3.4%
V13
 
3.4%
l12
 
3.1%
Other values (33)170
44.5%
Common
ValueCountFrequency (%)
22
88.0%
+1
 
4.0%
21
 
4.0%
.1
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII407
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
u38
 
9.3%
e33
 
8.1%
o27
 
6.6%
T24
 
5.9%
22
 
5.4%
Y19
 
4.7%
i19
 
4.7%
t14
 
3.4%
r13
 
3.2%
V13
 
3.2%
Other values (37)185
45.5%

_embedded.show.webChannel.country.name
Categorical

HIGH CORRELATION
MISSING

Distinct6
Distinct (%)20.7%
Missing24
Missing (%)45.3%
Memory size552.0 B
China
11 
United States
Norway
Korea, Republic of
Japan

Length

Max length18
Median length13
Mean length8.344827586
Min length5

Characters and Unicode

Total characters242
Distinct characters29
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)3.4%

Sample

1st rowKorea, Republic of
2nd rowChina
3rd rowChina
4th rowJapan
5th rowChina

Common Values

ValueCountFrequency (%)
China11
20.8%
United States6
 
11.3%
Norway5
 
9.4%
Korea, Republic of3
 
5.7%
Japan3
 
5.7%
Kazakhstan1
 
1.9%
(Missing)24
45.3%

Length

2022-09-05T21:41:57.813364image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:41:57.911879image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
china11
26.8%
united6
14.6%
states6
14.6%
norway5
12.2%
korea3
 
7.3%
republic3
 
7.3%
of3
 
7.3%
japan3
 
7.3%
kazakhstan1
 
2.4%

Most occurring characters

ValueCountFrequency (%)
a34
14.0%
n21
 
8.7%
i20
 
8.3%
t19
 
7.9%
e18
 
7.4%
12
 
5.0%
h12
 
5.0%
C11
 
4.5%
o11
 
4.5%
r8
 
3.3%
Other values (19)76
31.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter189
78.1%
Uppercase Letter38
 
15.7%
Space Separator12
 
5.0%
Other Punctuation3
 
1.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a34
18.0%
n21
11.1%
i20
10.6%
t19
10.1%
e18
9.5%
h12
 
6.3%
o11
 
5.8%
r8
 
4.2%
s7
 
3.7%
d6
 
3.2%
Other values (10)33
17.5%
Uppercase Letter
ValueCountFrequency (%)
C11
28.9%
S6
15.8%
U6
15.8%
N5
13.2%
K4
 
10.5%
J3
 
7.9%
R3
 
7.9%
Space Separator
ValueCountFrequency (%)
12
100.0%
Other Punctuation
ValueCountFrequency (%)
,3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin227
93.8%
Common15
 
6.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a34
15.0%
n21
 
9.3%
i20
 
8.8%
t19
 
8.4%
e18
 
7.9%
h12
 
5.3%
C11
 
4.8%
o11
 
4.8%
r8
 
3.5%
s7
 
3.1%
Other values (17)66
29.1%
Common
ValueCountFrequency (%)
12
80.0%
,3
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII242
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a34
14.0%
n21
 
8.7%
i20
 
8.3%
t19
 
7.9%
e18
 
7.4%
12
 
5.0%
h12
 
5.0%
C11
 
4.5%
o11
 
4.5%
r8
 
3.3%
Other values (19)76
31.4%

_embedded.show.webChannel.country.code
Categorical

HIGH CORRELATION
MISSING

Distinct6
Distinct (%)20.7%
Missing24
Missing (%)45.3%
Memory size552.0 B
CN
11 
US
NO
KR
JP

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters58
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)3.4%

Sample

1st rowKR
2nd rowCN
3rd rowCN
4th rowJP
5th rowCN

Common Values

ValueCountFrequency (%)
CN11
20.8%
US6
 
11.3%
NO5
 
9.4%
KR3
 
5.7%
JP3
 
5.7%
KZ1
 
1.9%
(Missing)24
45.3%

Length

2022-09-05T21:41:58.003601image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:41:58.096305image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
cn11
37.9%
us6
20.7%
no5
17.2%
kr3
 
10.3%
jp3
 
10.3%
kz1
 
3.4%

Most occurring characters

ValueCountFrequency (%)
N16
27.6%
C11
19.0%
U6
 
10.3%
S6
 
10.3%
O5
 
8.6%
K4
 
6.9%
R3
 
5.2%
J3
 
5.2%
P3
 
5.2%
Z1
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter58
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N16
27.6%
C11
19.0%
U6
 
10.3%
S6
 
10.3%
O5
 
8.6%
K4
 
6.9%
R3
 
5.2%
J3
 
5.2%
P3
 
5.2%
Z1
 
1.7%

Most occurring scripts

ValueCountFrequency (%)
Latin58
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N16
27.6%
C11
19.0%
U6
 
10.3%
S6
 
10.3%
O5
 
8.6%
K4
 
6.9%
R3
 
5.2%
J3
 
5.2%
P3
 
5.2%
Z1
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII58
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N16
27.6%
C11
19.0%
U6
 
10.3%
S6
 
10.3%
O5
 
8.6%
K4
 
6.9%
R3
 
5.2%
J3
 
5.2%
P3
 
5.2%
Z1
 
1.7%

_embedded.show.webChannel.country.timezone
Categorical

HIGH CORRELATION
MISSING

Distinct6
Distinct (%)20.7%
Missing24
Missing (%)45.3%
Memory size552.0 B
Asia/Shanghai
11 
America/New_York
Europe/Oslo
Asia/Seoul
Asia/Tokyo

Length

Max length16
Median length14
Mean length12.68965517
Min length10

Characters and Unicode

Total characters368
Distinct characters29
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)3.4%

Sample

1st rowAsia/Seoul
2nd rowAsia/Shanghai
3rd rowAsia/Shanghai
4th rowAsia/Tokyo
5th rowAsia/Shanghai

Common Values

ValueCountFrequency (%)
Asia/Shanghai11
20.8%
America/New_York6
 
11.3%
Europe/Oslo5
 
9.4%
Asia/Seoul3
 
5.7%
Asia/Tokyo3
 
5.7%
Asia/Qyzylorda1
 
1.9%
(Missing)24
45.3%

Length

2022-09-05T21:41:58.182978image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:41:58.279344image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
asia/shanghai11
37.9%
america/new_york6
20.7%
europe/oslo5
17.2%
asia/seoul3
 
10.3%
asia/tokyo3
 
10.3%
asia/qyzylorda1
 
3.4%

Most occurring characters

ValueCountFrequency (%)
a47
12.8%
i35
 
9.5%
/29
 
7.9%
o26
 
7.1%
A24
 
6.5%
s23
 
6.2%
h22
 
6.0%
e20
 
5.4%
r18
 
4.9%
S14
 
3.8%
Other values (19)110
29.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter269
73.1%
Uppercase Letter64
 
17.4%
Other Punctuation29
 
7.9%
Connector Punctuation6
 
1.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a47
17.5%
i35
13.0%
o26
9.7%
s23
8.6%
h22
8.2%
e20
7.4%
r18
 
6.7%
n11
 
4.1%
g11
 
4.1%
l9
 
3.3%
Other values (9)47
17.5%
Uppercase Letter
ValueCountFrequency (%)
A24
37.5%
S14
21.9%
Y6
 
9.4%
N6
 
9.4%
E5
 
7.8%
O5
 
7.8%
T3
 
4.7%
Q1
 
1.6%
Other Punctuation
ValueCountFrequency (%)
/29
100.0%
Connector Punctuation
ValueCountFrequency (%)
_6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin333
90.5%
Common35
 
9.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
a47
14.1%
i35
 
10.5%
o26
 
7.8%
A24
 
7.2%
s23
 
6.9%
h22
 
6.6%
e20
 
6.0%
r18
 
5.4%
S14
 
4.2%
n11
 
3.3%
Other values (17)93
27.9%
Common
ValueCountFrequency (%)
/29
82.9%
_6
 
17.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII368
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a47
12.8%
i35
 
9.5%
/29
 
7.9%
o26
 
7.1%
A24
 
6.5%
s23
 
6.2%
h22
 
6.0%
e20
 
5.4%
r18
 
4.9%
S14
 
3.8%
Other values (19)110
29.9%

_embedded.show.webChannel.officialSite
Categorical

HIGH CORRELATION
MISSING

Distinct11
Distinct (%)50.0%
Missing31
Missing (%)58.5%
Memory size552.0 B
https://www.youtube.com
https://v.qq.com/
https://www.netflix.com/
https://www.iq.com/
https://www.vlive.tv/home
Other values (6)

Length

Max length30
Median length26
Mean length22.36363636
Min length17

Characters and Unicode

Total characters492
Distinct characters26
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)31.8%

Sample

1st rowhttps://www.vlive.tv/home
2nd rowhttps://v.qq.com/
3rd rowhttps://v.qq.com/
4th rowhttps://tv.kakao.com/top
5th rowhttps://tv.naver.com/

Common Values

ValueCountFrequency (%)
https://www.youtube.com9
 
17.0%
https://v.qq.com/2
 
3.8%
https://www.netflix.com/2
 
3.8%
https://www.iq.com/2
 
3.8%
https://www.vlive.tv/home1
 
1.9%
https://tv.kakao.com/top1
 
1.9%
https://tv.naver.com/1
 
1.9%
https://www.linetv.tw/1
 
1.9%
https://www.discoveryplus.com/1
 
1.9%
https://www.primevideo.com1
 
1.9%
(Missing)31
58.5%

Length

2022-09-05T21:41:58.371922image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.youtube.com9
40.9%
https://v.qq.com2
 
9.1%
https://www.netflix.com2
 
9.1%
https://www.iq.com2
 
9.1%
https://www.vlive.tv/home1
 
4.5%
https://tv.kakao.com/top1
 
4.5%
https://tv.naver.com1
 
4.5%
https://www.linetv.tw1
 
4.5%
https://www.discoveryplus.com1
 
4.5%
https://www.primevideo.com1
 
4.5%

Most occurring characters

ValueCountFrequency (%)
t62
12.6%
/56
11.4%
w53
10.8%
.43
 
8.7%
o33
 
6.7%
p26
 
5.3%
s24
 
4.9%
h23
 
4.7%
:22
 
4.5%
m21
 
4.3%
Other values (16)129
26.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter371
75.4%
Other Punctuation121
 
24.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t62
16.7%
w53
14.3%
o33
8.9%
p26
 
7.0%
s24
 
6.5%
h23
 
6.2%
m21
 
5.7%
c20
 
5.4%
e19
 
5.1%
u19
 
5.1%
Other values (13)71
19.1%
Other Punctuation
ValueCountFrequency (%)
/56
46.3%
.43
35.5%
:22
 
18.2%

Most occurring scripts

ValueCountFrequency (%)
Latin371
75.4%
Common121
 
24.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t62
16.7%
w53
14.3%
o33
8.9%
p26
 
7.0%
s24
 
6.5%
h23
 
6.2%
m21
 
5.7%
c20
 
5.4%
e19
 
5.1%
u19
 
5.1%
Other values (13)71
19.1%
Common
ValueCountFrequency (%)
/56
46.3%
.43
35.5%
:22
 
18.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII492
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t62
12.6%
/56
11.4%
w53
10.8%
.43
 
8.7%
o33
 
6.7%
p26
 
5.3%
s24
 
4.9%
h23
 
4.7%
:22
 
4.5%
m21
 
4.3%
Other values (16)129
26.2%

_embedded.show.dvdCountry
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing53
Missing (%)100.0%
Memory size552.0 B

_embedded.show.externals.tvrage
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)50.0%
Missing51
Missing (%)96.2%
Memory size552.0 B
34149.0

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters14
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row34149.0
2nd row34149.0

Common Values

ValueCountFrequency (%)
34149.02
 
3.8%
(Missing)51
96.2%

Length

2022-09-05T21:41:58.466805image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:41:58.552755image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
34149.02
100.0%

Most occurring characters

ValueCountFrequency (%)
44
28.6%
32
14.3%
12
14.3%
92
14.3%
.2
14.3%
02
14.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number12
85.7%
Other Punctuation2
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
44
33.3%
32
16.7%
12
16.7%
92
16.7%
02
16.7%
Other Punctuation
ValueCountFrequency (%)
.2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common14
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
44
28.6%
32
14.3%
12
14.3%
92
14.3%
.2
14.3%
02
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII14
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
44
28.6%
32
14.3%
12
14.3%
92
14.3%
.2
14.3%
02
14.3%

_embedded.show.externals.thetvdb
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct34
Distinct (%)89.5%
Missing15
Missing (%)28.3%
Infinite0
Infinite (%)0.0%
Mean360036.7895
Minimum257720
Maximum397581
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size552.0 B
2022-09-05T21:41:58.632086image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum257720
5-th percentile263057.15
Q1333903.5
median378406
Q3388841.5
95-th percentile393476.05
Maximum397581
Range139861
Interquartile range (IQR)54938

Descriptive statistics

Standard deviation41795.38931
Coefficient of variation (CV)0.1160864404
Kurtosis1.026416046
Mean360036.7895
Median Absolute Deviation (MAD)12794.5
Skewness-1.431119836
Sum13681398
Variance1746854568
MonotonicityNot monotonic
2022-09-05T21:41:58.732537image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
3932292
 
3.8%
3310952
 
3.8%
3871522
 
3.8%
2577202
 
3.8%
3915281
 
1.9%
3776251
 
1.9%
3948761
 
1.9%
3865771
 
1.9%
3726401
 
1.9%
3699881
 
1.9%
Other values (24)24
45.3%
(Missing)15
28.3%
ValueCountFrequency (%)
2577202
3.8%
2639991
1.9%
2651931
1.9%
3166901
1.9%
3226731
1.9%
3227211
1.9%
3229061
1.9%
3310952
3.8%
3423291
1.9%
3554521
1.9%
ValueCountFrequency (%)
3975811
1.9%
3948761
1.9%
3932292
3.8%
3926491
1.9%
3915281
1.9%
3908731
1.9%
3894171
1.9%
3889191
1.9%
3888981
1.9%
3886721
1.9%

_embedded.show.externals.imdb
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct20
Distinct (%)87.0%
Missing30
Missing (%)56.6%
Memory size552.0 B
tt8871128
tt7057262
tt13175760
tt12457946
 
1
tt12605636
 
1
Other values (15)
15 

Length

Max length10
Median length10
Mean length9.608695652
Min length9

Characters and Unicode

Total characters221
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)73.9%

Sample

1st rowtt10784214
2nd rowtt13375866
3rd rowtt8871128
4th rowtt8871128
5th rowtt10960302

Common Values

ValueCountFrequency (%)
tt88711282
 
3.8%
tt70572622
 
3.8%
tt131757602
 
3.8%
tt124579461
 
1.9%
tt126056361
 
1.9%
tt135107341
 
1.9%
tt133995381
 
1.9%
tt125849001
 
1.9%
tt110111041
 
1.9%
tt30662421
 
1.9%
Other values (10)10
 
18.9%
(Missing)30
56.6%

Length

2022-09-05T21:41:58.826708image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tt88711282
 
8.7%
tt131757602
 
8.7%
tt70572622
 
8.7%
tt140284101
 
4.3%
tt133758661
 
4.3%
tt109603021
 
4.3%
tt114923201
 
4.3%
tt63440821
 
4.3%
tt89298261
 
4.3%
tt107842141
 
4.3%
Other values (10)10
43.5%

Most occurring characters

ValueCountFrequency (%)
t46
20.8%
129
13.1%
221
9.5%
020
9.0%
819
8.6%
418
 
8.1%
617
 
7.7%
714
 
6.3%
514
 
6.3%
314
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number175
79.2%
Lowercase Letter46
 
20.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
129
16.6%
221
12.0%
020
11.4%
819
10.9%
418
10.3%
617
9.7%
714
8.0%
514
8.0%
314
8.0%
99
 
5.1%
Lowercase Letter
ValueCountFrequency (%)
t46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common175
79.2%
Latin46
 
20.8%

Most frequent character per script

Common
ValueCountFrequency (%)
129
16.6%
221
12.0%
020
11.4%
819
10.9%
418
10.3%
617
9.7%
714
8.0%
514
8.0%
314
8.0%
99
 
5.1%
Latin
ValueCountFrequency (%)
t46
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII221
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t46
20.8%
129
13.1%
221
9.5%
020
9.0%
819
8.6%
418
 
8.1%
617
 
7.7%
714
 
6.3%
514
 
6.3%
314
 
6.3%

_embedded.show.image.medium
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct41
Distinct (%)82.0%
Missing3
Missing (%)5.7%
Memory size552.0 B
https://static.tvmaze.com/uploads/images/medium_portrait/289/722651.jpg
https://static.tvmaze.com/uploads/images/medium_portrait/291/729462.jpg
 
2
https://static.tvmaze.com/uploads/images/medium_portrait/291/729820.jpg
 
2
https://static.tvmaze.com/uploads/images/medium_portrait/277/693739.jpg
 
2
https://static.tvmaze.com/uploads/images/medium_portrait/398/996679.jpg
 
2
Other values (36)
38 

Length

Max length72
Median length71
Mean length71.16
Min length71

Characters and Unicode

Total characters3558
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)68.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_portrait/190/476668.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/150/375304.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/270/675333.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/268/670796.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/414/1036502.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/289/722651.jpg4
 
7.5%
https://static.tvmaze.com/uploads/images/medium_portrait/291/729462.jpg2
 
3.8%
https://static.tvmaze.com/uploads/images/medium_portrait/291/729820.jpg2
 
3.8%
https://static.tvmaze.com/uploads/images/medium_portrait/277/693739.jpg2
 
3.8%
https://static.tvmaze.com/uploads/images/medium_portrait/398/996679.jpg2
 
3.8%
https://static.tvmaze.com/uploads/images/medium_portrait/387/968749.jpg2
 
3.8%
https://static.tvmaze.com/uploads/images/medium_portrait/255/639532.jpg2
 
3.8%
https://static.tvmaze.com/uploads/images/medium_portrait/370/926987.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_portrait/403/1008990.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_portrait/264/662342.jpg1
 
1.9%
Other values (31)31
58.5%
(Missing)3
 
5.7%

Length

2022-09-05T21:41:58.914212image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/289/722651.jpg4
 
8.0%
https://static.tvmaze.com/uploads/images/medium_portrait/291/729820.jpg2
 
4.0%
https://static.tvmaze.com/uploads/images/medium_portrait/277/693739.jpg2
 
4.0%
https://static.tvmaze.com/uploads/images/medium_portrait/398/996679.jpg2
 
4.0%
https://static.tvmaze.com/uploads/images/medium_portrait/387/968749.jpg2
 
4.0%
https://static.tvmaze.com/uploads/images/medium_portrait/255/639532.jpg2
 
4.0%
https://static.tvmaze.com/uploads/images/medium_portrait/291/729462.jpg2
 
4.0%
https://static.tvmaze.com/uploads/images/medium_portrait/121/302950.jpg1
 
2.0%
https://static.tvmaze.com/uploads/images/medium_portrait/270/675333.jpg1
 
2.0%
https://static.tvmaze.com/uploads/images/medium_portrait/268/670796.jpg1
 
2.0%
Other values (31)31
62.0%

Most occurring characters

ValueCountFrequency (%)
t350
 
9.8%
/350
 
9.8%
a250
 
7.0%
m250
 
7.0%
p200
 
5.6%
s200
 
5.6%
i200
 
5.6%
o150
 
4.2%
.150
 
4.2%
e150
 
4.2%
Other values (22)1308
36.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2500
70.3%
Other Punctuation550
 
15.5%
Decimal Number458
 
12.9%
Connector Punctuation50
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t350
14.0%
a250
10.0%
m250
10.0%
p200
 
8.0%
s200
 
8.0%
i200
 
8.0%
o150
 
6.0%
e150
 
6.0%
g100
 
4.0%
u100
 
4.0%
Other values (8)550
22.0%
Decimal Number
ValueCountFrequency (%)
966
14.4%
263
13.8%
653
11.6%
751
11.1%
045
9.8%
140
8.7%
339
8.5%
837
8.1%
433
7.2%
531
6.8%
Other Punctuation
ValueCountFrequency (%)
/350
63.6%
.150
27.3%
:50
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_50
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2500
70.3%
Common1058
29.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
t350
14.0%
a250
10.0%
m250
10.0%
p200
 
8.0%
s200
 
8.0%
i200
 
8.0%
o150
 
6.0%
e150
 
6.0%
g100
 
4.0%
u100
 
4.0%
Other values (8)550
22.0%
Common
ValueCountFrequency (%)
/350
33.1%
.150
14.2%
966
 
6.2%
263
 
6.0%
653
 
5.0%
751
 
4.8%
_50
 
4.7%
:50
 
4.7%
045
 
4.3%
140
 
3.8%
Other values (4)140
 
13.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII3558
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t350
 
9.8%
/350
 
9.8%
a250
 
7.0%
m250
 
7.0%
p200
 
5.6%
s200
 
5.6%
i200
 
5.6%
o150
 
4.2%
.150
 
4.2%
e150
 
4.2%
Other values (22)1308
36.8%

_embedded.show.image.original
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct41
Distinct (%)82.0%
Missing3
Missing (%)5.7%
Memory size552.0 B
https://static.tvmaze.com/uploads/images/original_untouched/289/722651.jpg
https://static.tvmaze.com/uploads/images/original_untouched/291/729462.jpg
 
2
https://static.tvmaze.com/uploads/images/original_untouched/291/729820.jpg
 
2
https://static.tvmaze.com/uploads/images/original_untouched/277/693739.jpg
 
2
https://static.tvmaze.com/uploads/images/original_untouched/398/996679.jpg
 
2
Other values (36)
38 

Length

Max length75
Median length74
Mean length74.16
Min length74

Characters and Unicode

Total characters3708
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)68.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/190/476668.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/150/375304.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/270/675333.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/268/670796.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/414/1036502.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/289/722651.jpg4
 
7.5%
https://static.tvmaze.com/uploads/images/original_untouched/291/729462.jpg2
 
3.8%
https://static.tvmaze.com/uploads/images/original_untouched/291/729820.jpg2
 
3.8%
https://static.tvmaze.com/uploads/images/original_untouched/277/693739.jpg2
 
3.8%
https://static.tvmaze.com/uploads/images/original_untouched/398/996679.jpg2
 
3.8%
https://static.tvmaze.com/uploads/images/original_untouched/387/968749.jpg2
 
3.8%
https://static.tvmaze.com/uploads/images/original_untouched/255/639532.jpg2
 
3.8%
https://static.tvmaze.com/uploads/images/original_untouched/370/926987.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/403/1008990.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/264/662342.jpg1
 
1.9%
Other values (31)31
58.5%
(Missing)3
 
5.7%

Length

2022-09-05T21:41:59.010235image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/289/722651.jpg4
 
8.0%
https://static.tvmaze.com/uploads/images/original_untouched/291/729820.jpg2
 
4.0%
https://static.tvmaze.com/uploads/images/original_untouched/277/693739.jpg2
 
4.0%
https://static.tvmaze.com/uploads/images/original_untouched/398/996679.jpg2
 
4.0%
https://static.tvmaze.com/uploads/images/original_untouched/387/968749.jpg2
 
4.0%
https://static.tvmaze.com/uploads/images/original_untouched/255/639532.jpg2
 
4.0%
https://static.tvmaze.com/uploads/images/original_untouched/291/729462.jpg2
 
4.0%
https://static.tvmaze.com/uploads/images/original_untouched/121/302950.jpg1
 
2.0%
https://static.tvmaze.com/uploads/images/original_untouched/270/675333.jpg1
 
2.0%
https://static.tvmaze.com/uploads/images/original_untouched/268/670796.jpg1
 
2.0%
Other values (31)31
62.0%

Most occurring characters

ValueCountFrequency (%)
/350
 
9.4%
t300
 
8.1%
a250
 
6.7%
s200
 
5.4%
i200
 
5.4%
o200
 
5.4%
p150
 
4.0%
c150
 
4.0%
.150
 
4.0%
g150
 
4.0%
Other values (23)1608
43.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2650
71.5%
Other Punctuation550
 
14.8%
Decimal Number458
 
12.4%
Connector Punctuation50
 
1.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t300
 
11.3%
a250
 
9.4%
s200
 
7.5%
i200
 
7.5%
o200
 
7.5%
p150
 
5.7%
c150
 
5.7%
g150
 
5.7%
m150
 
5.7%
e150
 
5.7%
Other values (9)750
28.3%
Decimal Number
ValueCountFrequency (%)
966
14.4%
263
13.8%
653
11.6%
751
11.1%
045
9.8%
140
8.7%
339
8.5%
837
8.1%
433
7.2%
531
6.8%
Other Punctuation
ValueCountFrequency (%)
/350
63.6%
.150
27.3%
:50
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_50
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2650
71.5%
Common1058
 
28.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
t300
 
11.3%
a250
 
9.4%
s200
 
7.5%
i200
 
7.5%
o200
 
7.5%
p150
 
5.7%
c150
 
5.7%
g150
 
5.7%
m150
 
5.7%
e150
 
5.7%
Other values (9)750
28.3%
Common
ValueCountFrequency (%)
/350
33.1%
.150
14.2%
966
 
6.2%
263
 
6.0%
653
 
5.0%
751
 
4.8%
:50
 
4.7%
_50
 
4.7%
045
 
4.3%
140
 
3.8%
Other values (4)140
 
13.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII3708
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/350
 
9.4%
t300
 
8.1%
a250
 
6.7%
s200
 
5.4%
i200
 
5.4%
o200
 
5.4%
p150
 
4.0%
c150
 
4.0%
.150
 
4.0%
g150
 
4.0%
Other values (23)1608
43.4%

_embedded.show.summary
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct42
Distinct (%)82.4%
Missing2
Missing (%)3.8%
Memory size552.0 B
<p>Two boggling mysteries have occured in a small town in Xinan. A female police captain joins hands with a young detective to conduct an investigation. Although a clear motive can be seen, the two discover a series of unknown secrets.</p><p>One case involves a late-night ride hailed through an online platform that goes terribly wrong. As more and more clues resurface, the cases in the hands of the police hands become complicated and entangled. In a desperate attempt to find the real culprit, events closely link the past, present and future of the small town.</p>
<p>Curious about his uncle's past, Wu Xie watched a mysterious videotape, only to find himself mixed up in an elaborate conspiracy. In his adventures, he encountered Zhang Qi Ling, Xie Yu Chen, and others. </p>
 
2
<p>The story happens at the end of the Tang Dynasty, when Zhu Wen usurps the throne and establishes the Later Liang Dynasty, and he's known as Emperor Taizu. Ma Zhai Xing (Li Qin) is the daughter of an official and as a child, she befriends a young boy (Darren Wang) who lives in the mountain. One day when he saves a wolf, he accidentally falls over the cliff and is rescued by Zhu Wen. The authoritative figure adopts him as a godson and gives him the title Bo Wang. Ten years later, he saves the female lead per chance and finds her courage and intelligence resonant, and she likes that while he's in a position of power, he still has humility and kindness. She encourages him to fight for justice and he begins that journey by helping the people, stopping throne fights, etc. Even when they have conflicts, they will face those frankly. As they overcome obstacles and fight for justice, feelings deepen and they are able to reap their own happiness by each other's side.</p>
 
2
<p>‎The fashion company faced a crisis. Sun Chi, the young owner of the company, at a critical moment took over the management and became the new CEO. He promised his father that in three months he would be able to promote the project "promoting fashion" that will help to get out of the crisis. ‎ </p><p>‎Gio Intao, who wanted to be the queen of the fashion industry, by coincidence got into the company and became subordinate to the "devil", a young gene. Director Sun Chi.‎   </p><p>‎Sun Chi and Xiao Intao led a fashion company to resolve the crisis and open new markets, allowing Chinese fashion brands to enter the global market step by step. At the same time, they begin to feel each other.‎</p>
 
2
<p><b>Detention</b> starts at Greenwood High School in the 1990s. Yunxiang Liu, a transfer student, steps into the forbidden area on the campus by accident, where she encounters the ghost of Ruixin Fang. Fang later unveils the hidden history and trauma over the past 30 years, and how a group of young students and teachers were persecuted as they fought for freedom in the era of censorship. Their stories keep coming back to the school like haunting nightmares, waiting to be told and revealed.  </p>
 
2
Other values (37)
39 

Length

Max length1620
Median length370
Mean length401.1176471
Min length75

Characters and Unicode

Total characters20457
Distinct characters80
Distinct categories11 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)68.6%

Sample

1st row<p><b>Sim for You</b> is a reality series that chronicles each EXO member's life and reveal stories from their everyday life as a series.</p>
2nd row<p>Tang San spent his life in the Tang Outer Sect, dedicated to the creation and mastery of hidden weapons. Once he stole the secret lore of the Inner Sect to reach the pinnacle of his art, his only way out was death. But after throwing himself off the deadly Hell's Peak he was reborn in a different world, the world of Douluo Dalu, a world where every person has a spirit of their own, and those with powerful spirits can practice their spirit power to rise and become Spirit Masters.<br /><br />The spirit that awakens within Tang San is Blue Silver Grass, a useless spirit. Can he overcome the difficulties to reach the high ranks of Spirit Masters and bring the glory of the Tang Sect into this new world?</p>
3rd row<p>In ancient Shenzhou, humans and demons had been in constant dispute for thousands of years. The demon princess from Tushan, Bai Binglan, and the human Zhang Kuangyun met each other due to a misunderstanding. In order to investigate the enemy country, Bai Binglan became Zhang Kuangyun's companion. As they travel together, Zhang Kuangyun discovers a conspiracy...</p>
4th row<p>"Have you heard? The rubbish Heaven Official is having an affair with the ghost realm's number one bigshot!"</p><p>Eight hundred years ago, Xie Lian was the Crown Prince of the Xian Le kingdom; one who was beloved by his citizens and the darling of the world. Unsurprisingly, he ascended to the Heavens at a very young age. Now, eight hundred years later, Xie Lian ascends to the Heavens for the third time as the laughing stock of all three realms. On his first task as a god, he meets a mysterious demon who rules the ghosts and terrifies the Heavens... yet unbeknownst to Xie Lian, this demon king has been paying attention to him for a very, very long time.</p>
5th row<p>The story happens at the end of the Tang Dynasty, when Zhu Wen usurps the throne and establishes the Later Liang Dynasty, and he's known as Emperor Taizu. Ma Zhai Xing (Li Qin) is the daughter of an official and as a child, she befriends a young boy (Darren Wang) who lives in the mountain. One day when he saves a wolf, he accidentally falls over the cliff and is rescued by Zhu Wen. The authoritative figure adopts him as a godson and gives him the title Bo Wang. Ten years later, he saves the female lead per chance and finds her courage and intelligence resonant, and she likes that while he's in a position of power, he still has humility and kindness. She encourages him to fight for justice and he begins that journey by helping the people, stopping throne fights, etc. Even when they have conflicts, they will face those frankly. As they overcome obstacles and fight for justice, feelings deepen and they are able to reap their own happiness by each other's side.</p>

Common Values

ValueCountFrequency (%)
<p>Two boggling mysteries have occured in a small town in Xinan. A female police captain joins hands with a young detective to conduct an investigation. Although a clear motive can be seen, the two discover a series of unknown secrets.</p><p>One case involves a late-night ride hailed through an online platform that goes terribly wrong. As more and more clues resurface, the cases in the hands of the police hands become complicated and entangled. In a desperate attempt to find the real culprit, events closely link the past, present and future of the small town.</p>4
 
7.5%
<p>Curious about his uncle's past, Wu Xie watched a mysterious videotape, only to find himself mixed up in an elaborate conspiracy. In his adventures, he encountered Zhang Qi Ling, Xie Yu Chen, and others. </p>2
 
3.8%
<p>The story happens at the end of the Tang Dynasty, when Zhu Wen usurps the throne and establishes the Later Liang Dynasty, and he's known as Emperor Taizu. Ma Zhai Xing (Li Qin) is the daughter of an official and as a child, she befriends a young boy (Darren Wang) who lives in the mountain. One day when he saves a wolf, he accidentally falls over the cliff and is rescued by Zhu Wen. The authoritative figure adopts him as a godson and gives him the title Bo Wang. Ten years later, he saves the female lead per chance and finds her courage and intelligence resonant, and she likes that while he's in a position of power, he still has humility and kindness. She encourages him to fight for justice and he begins that journey by helping the people, stopping throne fights, etc. Even when they have conflicts, they will face those frankly. As they overcome obstacles and fight for justice, feelings deepen and they are able to reap their own happiness by each other's side.</p>2
 
3.8%
<p>‎The fashion company faced a crisis. Sun Chi, the young owner of the company, at a critical moment took over the management and became the new CEO. He promised his father that in three months he would be able to promote the project "promoting fashion" that will help to get out of the crisis. ‎ </p><p>‎Gio Intao, who wanted to be the queen of the fashion industry, by coincidence got into the company and became subordinate to the "devil", a young gene. Director Sun Chi.‎   </p><p>‎Sun Chi and Xiao Intao led a fashion company to resolve the crisis and open new markets, allowing Chinese fashion brands to enter the global market step by step. At the same time, they begin to feel each other.‎</p>2
 
3.8%
<p><b>Detention</b> starts at Greenwood High School in the 1990s. Yunxiang Liu, a transfer student, steps into the forbidden area on the campus by accident, where she encounters the ghost of Ruixin Fang. Fang later unveils the hidden history and trauma over the past 30 years, and how a group of young students and teachers were persecuted as they fought for freedom in the era of censorship. Their stories keep coming back to the school like haunting nightmares, waiting to be told and revealed.  </p>2
 
3.8%
<p>7 artists spend eight days together at a farm outside the city of Moss, where each artist attempts to do their own version of another artists well-known songs, with each person getting an episode featuring all of their songs being performed by the other musicians.</p>2
 
3.8%
<p>Televised undercard bouts from UFC Pay-Per-Views and UFC Fight Nights exclusively on UFC Fight Pass.</p>2
 
3.8%
<p>The future-fantasy world of Remnant is filled with ravenous monsters, treacherous terrain, and more villains than you can shake a sniper-scythe at. Fortunately, Beacon Academy is training Huntsman and Huntresses to battle the evils of the world, and Ruby, Weiss, Blake, and Yang are ready for their first day of class.</p>1
 
1.9%
<p>Living with her aunt, kind-hearted Thourayya leads a simple life, but her world is upended when she crosses paths with the handsome and ambitious Fares.</p>1
 
1.9%
<p><b>War Against Humanity</b> is a sub-series of "World War Two: Week by Week" focusing on war crimes and atrocities from all sides of the conflict that aren't described in detail in regular week by week episodes.</p>1
 
1.9%
Other values (32)32
60.4%
(Missing)2
 
3.8%

Length

2022-09-05T21:41:59.122709image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the226
 
6.6%
and134
 
3.9%
a112
 
3.3%
of91
 
2.7%
to88
 
2.6%
in69
 
2.0%
is37
 
1.1%
as30
 
0.9%
he30
 
0.9%
with30
 
0.9%
Other values (1198)2558
75.1%

Most occurring characters

ValueCountFrequency (%)
3343
16.3%
e1897
 
9.3%
t1338
 
6.5%
a1304
 
6.4%
n1223
 
6.0%
o1190
 
5.8%
i1132
 
5.5%
s1074
 
5.3%
r890
 
4.4%
h845
 
4.1%
Other values (70)6221
30.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter15508
75.8%
Space Separator3360
 
16.4%
Uppercase Letter587
 
2.9%
Other Punctuation562
 
2.7%
Math Symbol348
 
1.7%
Dash Punctuation38
 
0.2%
Decimal Number31
 
0.2%
Format12
 
0.1%
Open Punctuation5
 
< 0.1%
Close Punctuation5
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e1897
12.2%
t1338
 
8.6%
a1304
 
8.4%
n1223
 
7.9%
o1190
 
7.7%
i1132
 
7.3%
s1074
 
6.9%
r890
 
5.7%
h845
 
5.4%
d605
 
3.9%
Other values (17)4010
25.9%
Uppercase Letter
ValueCountFrequency (%)
T73
 
12.4%
S47
 
8.0%
A40
 
6.8%
W39
 
6.6%
H31
 
5.3%
I31
 
5.3%
C31
 
5.3%
L31
 
5.3%
F27
 
4.6%
O24
 
4.1%
Other values (16)213
36.3%
Other Punctuation
ValueCountFrequency (%)
,213
37.9%
.166
29.5%
/89
15.8%
'36
 
6.4%
"30
 
5.3%
!14
 
2.5%
?5
 
0.9%
;4
 
0.7%
:4
 
0.7%
&1
 
0.2%
Decimal Number
ValueCountFrequency (%)
011
35.5%
25
16.1%
15
16.1%
95
16.1%
32
 
6.5%
72
 
6.5%
41
 
3.2%
Space Separator
ValueCountFrequency (%)
3343
99.5%
 17
 
0.5%
Math Symbol
ValueCountFrequency (%)
>174
50.0%
<174
50.0%
Dash Punctuation
ValueCountFrequency (%)
-31
81.6%
7
 
18.4%
Format
ValueCountFrequency (%)
12
100.0%
Open Punctuation
ValueCountFrequency (%)
(5
100.0%
Close Punctuation
ValueCountFrequency (%)
)5
100.0%
Initial Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin16095
78.7%
Common4362
 
21.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e1897
11.8%
t1338
 
8.3%
a1304
 
8.1%
n1223
 
7.6%
o1190
 
7.4%
i1132
 
7.0%
s1074
 
6.7%
r890
 
5.5%
h845
 
5.3%
d605
 
3.8%
Other values (43)4597
28.6%
Common
ValueCountFrequency (%)
3343
76.6%
,213
 
4.9%
>174
 
4.0%
<174
 
4.0%
.166
 
3.8%
/89
 
2.0%
'36
 
0.8%
-31
 
0.7%
"30
 
0.7%
 17
 
0.4%
Other values (17)89
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII20419
99.8%
Punctuation20
 
0.1%
None18
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3343
16.4%
e1897
 
9.3%
t1338
 
6.6%
a1304
 
6.4%
n1223
 
6.0%
o1190
 
5.8%
i1132
 
5.5%
s1074
 
5.3%
r890
 
4.4%
h845
 
4.1%
Other values (65)6183
30.3%
None
ValueCountFrequency (%)
 17
94.4%
æ1
 
5.6%
Punctuation
ValueCountFrequency (%)
12
60.0%
7
35.0%
1
 
5.0%

_embedded.show.updated
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct44
Distinct (%)83.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1643306950
Minimum1607798027
Maximum1662307326
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size552.0 B
2022-09-05T21:41:59.229950image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1607798027
5-th percentile1609546915
Q11636362084
median1649178084
Q31655988055
95-th percentile1662243997
Maximum1662307326
Range54509299
Interquartile range (IQR)19625971

Descriptive statistics

Standard deviation17748708.28
Coefficient of variation (CV)0.0108006044
Kurtosis-0.4056190773
Mean1643306950
Median Absolute Deviation (MAD)9650544
Skewness-0.9686384603
Sum8.709526834 × 1010
Variance3.150166455 × 1014
MonotonicityNot monotonic
2022-09-05T21:41:59.346415image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
16545931514
 
7.5%
16482170292
 
3.8%
16098872012
 
3.8%
16465289862
 
3.8%
16096716402
 
3.8%
16559880552
 
3.8%
16491780842
 
3.8%
16404548121
 
1.9%
16622313551
 
1.9%
16152354381
 
1.9%
Other values (34)34
64.2%
ValueCountFrequency (%)
16077980271
1.9%
16084990071
1.9%
16093598271
1.9%
16096716402
3.8%
16098872012
3.8%
16114368421
1.9%
16152354381
1.9%
16238295291
1.9%
16238296751
1.9%
16284290411
1.9%
ValueCountFrequency (%)
16623073261
1.9%
16622756681
1.9%
16622629611
1.9%
16622313551
1.9%
16613637251
1.9%
16611090651
1.9%
16611067121
1.9%
16604017471
1.9%
16593728511
1.9%
16589222681
1.9%

_embedded.show._links.self.href
Categorical

HIGH CORRELATION
UNIFORM

Distinct44
Distinct (%)83.0%
Missing0
Missing (%)0.0%
Memory size552.0 B
https://api.tvmaze.com/shows/52451
 
4
https://api.tvmaze.com/shows/47912
 
2
https://api.tvmaze.com/shows/51125
 
2
https://api.tvmaze.com/shows/25294
 
2
https://api.tvmaze.com/shows/52782
 
2
Other values (39)
41 

Length

Max length34
Median length34
Mean length33.96226415
Min length33

Characters and Unicode

Total characters1800
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)69.8%

Sample

1st rowhttps://api.tvmaze.com/shows/41648
2nd rowhttps://api.tvmaze.com/shows/35551
3rd rowhttps://api.tvmaze.com/shows/49206
4th rowhttps://api.tvmaze.com/shows/49740
5th rowhttps://api.tvmaze.com/shows/51670

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/shows/524514
 
7.5%
https://api.tvmaze.com/shows/479122
 
3.8%
https://api.tvmaze.com/shows/511252
 
3.8%
https://api.tvmaze.com/shows/252942
 
3.8%
https://api.tvmaze.com/shows/527822
 
3.8%
https://api.tvmaze.com/shows/115022
 
3.8%
https://api.tvmaze.com/shows/528062
 
3.8%
https://api.tvmaze.com/shows/513141
 
1.9%
https://api.tvmaze.com/shows/579451
 
1.9%
https://api.tvmaze.com/shows/37341
 
1.9%
Other values (34)34
64.2%

Length

2022-09-05T21:41:59.448328image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/shows/524514
 
7.5%
https://api.tvmaze.com/shows/511252
 
3.8%
https://api.tvmaze.com/shows/252942
 
3.8%
https://api.tvmaze.com/shows/527822
 
3.8%
https://api.tvmaze.com/shows/115022
 
3.8%
https://api.tvmaze.com/shows/528062
 
3.8%
https://api.tvmaze.com/shows/479122
 
3.8%
https://api.tvmaze.com/shows/579561
 
1.9%
https://api.tvmaze.com/shows/492061
 
1.9%
https://api.tvmaze.com/shows/497401
 
1.9%
Other values (34)34
64.2%

Most occurring characters

ValueCountFrequency (%)
/212
 
11.8%
s159
 
8.8%
t159
 
8.8%
h106
 
5.9%
p106
 
5.9%
a106
 
5.9%
.106
 
5.9%
o106
 
5.9%
m106
 
5.9%
556
 
3.1%
Other values (16)578
32.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1166
64.8%
Other Punctuation371
 
20.6%
Decimal Number263
 
14.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s159
13.6%
t159
13.6%
h106
9.1%
p106
9.1%
a106
9.1%
o106
9.1%
m106
9.1%
e53
 
4.5%
w53
 
4.5%
c53
 
4.5%
Other values (3)159
13.6%
Decimal Number
ValueCountFrequency (%)
556
21.3%
431
11.8%
130
11.4%
229
11.0%
823
8.7%
022
 
8.4%
621
 
8.0%
920
 
7.6%
716
 
6.1%
315
 
5.7%
Other Punctuation
ValueCountFrequency (%)
/212
57.1%
.106
28.6%
:53
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin1166
64.8%
Common634
35.2%

Most frequent character per script

Common
ValueCountFrequency (%)
/212
33.4%
.106
16.7%
556
 
8.8%
:53
 
8.4%
431
 
4.9%
130
 
4.7%
229
 
4.6%
823
 
3.6%
022
 
3.5%
621
 
3.3%
Other values (3)51
 
8.0%
Latin
ValueCountFrequency (%)
s159
13.6%
t159
13.6%
h106
9.1%
p106
9.1%
a106
9.1%
o106
9.1%
m106
9.1%
e53
 
4.5%
w53
 
4.5%
c53
 
4.5%
Other values (3)159
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII1800
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/212
 
11.8%
s159
 
8.8%
t159
 
8.8%
h106
 
5.9%
p106
 
5.9%
a106
 
5.9%
.106
 
5.9%
o106
 
5.9%
m106
 
5.9%
556
 
3.1%
Other values (16)578
32.1%

_embedded.show._links.previousepisode.href
Categorical

HIGH CORRELATION
UNIFORM

Distinct44
Distinct (%)83.0%
Missing0
Missing (%)0.0%
Memory size552.0 B
https://api.tvmaze.com/episodes/1986174
 
4
https://api.tvmaze.com/episodes/1972591
 
2
https://api.tvmaze.com/episodes/1992714
 
2
https://api.tvmaze.com/episodes/2230458
 
2
https://api.tvmaze.com/episodes/1998584
 
2
Other values (39)
41 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters2067
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)69.8%

Sample

1st rowhttps://api.tvmaze.com/episodes/1988862
2nd rowhttps://api.tvmaze.com/episodes/2330393
3rd rowhttps://api.tvmaze.com/episodes/2386129
4th rowhttps://api.tvmaze.com/episodes/2377377
5th rowhttps://api.tvmaze.com/episodes/1993891

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19861744
 
7.5%
https://api.tvmaze.com/episodes/19725912
 
3.8%
https://api.tvmaze.com/episodes/19927142
 
3.8%
https://api.tvmaze.com/episodes/22304582
 
3.8%
https://api.tvmaze.com/episodes/19985842
 
3.8%
https://api.tvmaze.com/episodes/22490232
 
3.8%
https://api.tvmaze.com/episodes/20000832
 
3.8%
https://api.tvmaze.com/episodes/22074051
 
1.9%
https://api.tvmaze.com/episodes/23858501
 
1.9%
https://api.tvmaze.com/episodes/19829041
 
1.9%
Other values (34)34
64.2%

Length

2022-09-05T21:41:59.533464image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19861744
 
7.5%
https://api.tvmaze.com/episodes/19927142
 
3.8%
https://api.tvmaze.com/episodes/22304582
 
3.8%
https://api.tvmaze.com/episodes/19985842
 
3.8%
https://api.tvmaze.com/episodes/22490232
 
3.8%
https://api.tvmaze.com/episodes/20000832
 
3.8%
https://api.tvmaze.com/episodes/19725912
 
3.8%
https://api.tvmaze.com/episodes/21821181
 
1.9%
https://api.tvmaze.com/episodes/23861291
 
1.9%
https://api.tvmaze.com/episodes/23773771
 
1.9%
Other values (34)34
64.2%

Most occurring characters

ValueCountFrequency (%)
/212
 
10.3%
p159
 
7.7%
s159
 
7.7%
e159
 
7.7%
t159
 
7.7%
o106
 
5.1%
a106
 
5.1%
i106
 
5.1%
.106
 
5.1%
m106
 
5.1%
Other values (16)689
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1325
64.1%
Other Punctuation371
 
17.9%
Decimal Number371
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p159
12.0%
s159
12.0%
e159
12.0%
t159
12.0%
o106
8.0%
a106
8.0%
i106
8.0%
m106
8.0%
h53
 
4.0%
d53
 
4.0%
Other values (3)159
12.0%
Decimal Number
ValueCountFrequency (%)
267
18.1%
153
14.3%
944
11.9%
840
10.8%
337
10.0%
734
9.2%
030
8.1%
426
 
7.0%
620
 
5.4%
520
 
5.4%
Other Punctuation
ValueCountFrequency (%)
/212
57.1%
.106
28.6%
:53
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin1325
64.1%
Common742
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/212
28.6%
.106
14.3%
267
 
9.0%
153
 
7.1%
:53
 
7.1%
944
 
5.9%
840
 
5.4%
337
 
5.0%
734
 
4.6%
030
 
4.0%
Other values (3)66
 
8.9%
Latin
ValueCountFrequency (%)
p159
12.0%
s159
12.0%
e159
12.0%
t159
12.0%
o106
8.0%
a106
8.0%
i106
8.0%
m106
8.0%
h53
 
4.0%
d53
 
4.0%
Other values (3)159
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2067
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/212
 
10.3%
p159
 
7.7%
s159
 
7.7%
e159
 
7.7%
t159
 
7.7%
o106
 
5.1%
a106
 
5.1%
i106
 
5.1%
.106
 
5.1%
m106
 
5.1%
Other values (16)689
33.3%

_embedded.show._links.nextepisode.href
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct4
Distinct (%)100.0%
Missing49
Missing (%)92.5%
Memory size552.0 B
https://api.tvmaze.com/episodes/2330394
https://api.tvmaze.com/episodes/2377378
https://api.tvmaze.com/episodes/2373586
https://api.tvmaze.com/episodes/2379063

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters156
Distinct characters25
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/2330394
2nd rowhttps://api.tvmaze.com/episodes/2377378
3rd rowhttps://api.tvmaze.com/episodes/2373586
4th rowhttps://api.tvmaze.com/episodes/2379063

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/23303941
 
1.9%
https://api.tvmaze.com/episodes/23773781
 
1.9%
https://api.tvmaze.com/episodes/23735861
 
1.9%
https://api.tvmaze.com/episodes/23790631
 
1.9%
(Missing)49
92.5%

Length

2022-09-05T21:41:59.617276image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:41:59.709943image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/23303941
25.0%
https://api.tvmaze.com/episodes/23773781
25.0%
https://api.tvmaze.com/episodes/23735861
25.0%
https://api.tvmaze.com/episodes/23790631
25.0%

Most occurring characters

ValueCountFrequency (%)
/16
 
10.3%
e12
 
7.7%
p12
 
7.7%
s12
 
7.7%
t12
 
7.7%
39
 
5.8%
o8
 
5.1%
a8
 
5.1%
i8
 
5.1%
.8
 
5.1%
Other values (15)51
32.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter100
64.1%
Other Punctuation28
 
17.9%
Decimal Number28
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e12
12.0%
p12
12.0%
s12
12.0%
t12
12.0%
o8
8.0%
a8
8.0%
i8
8.0%
m8
8.0%
d4
 
4.0%
h4
 
4.0%
Other values (3)12
12.0%
Decimal Number
ValueCountFrequency (%)
39
32.1%
75
17.9%
24
14.3%
02
 
7.1%
92
 
7.1%
82
 
7.1%
62
 
7.1%
41
 
3.6%
51
 
3.6%
Other Punctuation
ValueCountFrequency (%)
/16
57.1%
.8
28.6%
:4
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin100
64.1%
Common56
35.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e12
12.0%
p12
12.0%
s12
12.0%
t12
12.0%
o8
8.0%
a8
8.0%
i8
8.0%
m8
8.0%
d4
 
4.0%
h4
 
4.0%
Other values (3)12
12.0%
Common
ValueCountFrequency (%)
/16
28.6%
39
16.1%
.8
14.3%
75
 
8.9%
24
 
7.1%
:4
 
7.1%
02
 
3.6%
92
 
3.6%
82
 
3.6%
62
 
3.6%
Other values (2)2
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII156
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/16
 
10.3%
e12
 
7.7%
p12
 
7.7%
s12
 
7.7%
t12
 
7.7%
39
 
5.8%
o8
 
5.1%
a8
 
5.1%
i8
 
5.1%
.8
 
5.1%
Other values (15)51
32.7%

image.medium
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct18
Distinct (%)100.0%
Missing35
Missing (%)66.0%
Memory size552.0 B
https://static.tvmaze.com/uploads/images/medium_landscape/288/721668.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/288/721362.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/288/722361.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/329/823875.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/288/722381.jpg
 
1
Other values (13)
13 

Length

Max length73
Median length72
Mean length72.11111111
Min length72

Characters and Unicode

Total characters1298
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_landscape/290/726346.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/288/721377.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/288/721378.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/361/903573.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/394/986669.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/288/721668.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_landscape/288/721362.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_landscape/288/722361.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_landscape/329/823875.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_landscape/288/722381.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_landscape/404/1010041.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_landscape/286/716997.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_landscape/329/823868.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_landscape/288/721666.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726346.jpg1
 
1.9%
Other values (8)8
 
15.1%
(Missing)35
66.0%

Length

2022-09-05T21:41:59.796620image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/288/721668.jpg1
 
5.6%
https://static.tvmaze.com/uploads/images/medium_landscape/288/721362.jpg1
 
5.6%
https://static.tvmaze.com/uploads/images/medium_landscape/288/721377.jpg1
 
5.6%
https://static.tvmaze.com/uploads/images/medium_landscape/288/721378.jpg1
 
5.6%
https://static.tvmaze.com/uploads/images/medium_landscape/361/903573.jpg1
 
5.6%
https://static.tvmaze.com/uploads/images/medium_landscape/394/986669.jpg1
 
5.6%
https://static.tvmaze.com/uploads/images/medium_landscape/288/720583.jpg1
 
5.6%
https://static.tvmaze.com/uploads/images/medium_landscape/290/725744.jpg1
 
5.6%
https://static.tvmaze.com/uploads/images/medium_landscape/288/721364.jpg1
 
5.6%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726346.jpg1
 
5.6%
Other values (8)8
44.4%

Most occurring characters

ValueCountFrequency (%)
/126
 
9.7%
a108
 
8.3%
s90
 
6.9%
m90
 
6.9%
t90
 
6.9%
p72
 
5.5%
e72
 
5.5%
i54
 
4.2%
c54
 
4.2%
.54
 
4.2%
Other values (22)488
37.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter918
70.7%
Other Punctuation198
 
15.3%
Decimal Number164
 
12.6%
Connector Punctuation18
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a108
11.8%
s90
9.8%
m90
9.8%
t90
9.8%
p72
 
7.8%
e72
 
7.8%
i54
 
5.9%
c54
 
5.9%
d54
 
5.9%
l36
 
3.9%
Other values (8)198
21.6%
Decimal Number
ValueCountFrequency (%)
231
18.9%
829
17.7%
720
12.2%
617
10.4%
316
9.8%
115
9.1%
011
 
6.7%
910
 
6.1%
410
 
6.1%
55
 
3.0%
Other Punctuation
ValueCountFrequency (%)
/126
63.6%
.54
27.3%
:18
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin918
70.7%
Common380
29.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a108
11.8%
s90
9.8%
m90
9.8%
t90
9.8%
p72
 
7.8%
e72
 
7.8%
i54
 
5.9%
c54
 
5.9%
d54
 
5.9%
l36
 
3.9%
Other values (8)198
21.6%
Common
ValueCountFrequency (%)
/126
33.2%
.54
14.2%
231
 
8.2%
829
 
7.6%
720
 
5.3%
_18
 
4.7%
:18
 
4.7%
617
 
4.5%
316
 
4.2%
115
 
3.9%
Other values (4)36
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII1298
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/126
 
9.7%
a108
 
8.3%
s90
 
6.9%
m90
 
6.9%
t90
 
6.9%
p72
 
5.5%
e72
 
5.5%
i54
 
4.2%
c54
 
4.2%
.54
 
4.2%
Other values (22)488
37.6%

image.original
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct18
Distinct (%)100.0%
Missing35
Missing (%)66.0%
Memory size552.0 B
https://static.tvmaze.com/uploads/images/original_untouched/288/721668.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/288/721362.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/288/722361.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/329/823875.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/288/722381.jpg
 
1
Other values (13)
13 

Length

Max length75
Median length74
Mean length74.11111111
Min length74

Characters and Unicode

Total characters1334
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/290/726346.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/288/721377.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/288/721378.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/361/903573.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/394/986669.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/288/721668.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/288/721362.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/288/722361.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/329/823875.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/288/722381.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/404/1010041.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/286/716997.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/329/823868.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/288/721666.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/290/726346.jpg1
 
1.9%
Other values (8)8
 
15.1%
(Missing)35
66.0%

Length

2022-09-05T21:41:59.883667image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/288/721668.jpg1
 
5.6%
https://static.tvmaze.com/uploads/images/original_untouched/288/721362.jpg1
 
5.6%
https://static.tvmaze.com/uploads/images/original_untouched/288/721377.jpg1
 
5.6%
https://static.tvmaze.com/uploads/images/original_untouched/288/721378.jpg1
 
5.6%
https://static.tvmaze.com/uploads/images/original_untouched/361/903573.jpg1
 
5.6%
https://static.tvmaze.com/uploads/images/original_untouched/394/986669.jpg1
 
5.6%
https://static.tvmaze.com/uploads/images/original_untouched/288/720583.jpg1
 
5.6%
https://static.tvmaze.com/uploads/images/original_untouched/290/725744.jpg1
 
5.6%
https://static.tvmaze.com/uploads/images/original_untouched/288/721364.jpg1
 
5.6%
https://static.tvmaze.com/uploads/images/original_untouched/290/726346.jpg1
 
5.6%
Other values (8)8
44.4%

Most occurring characters

ValueCountFrequency (%)
/126
 
9.4%
t108
 
8.1%
a90
 
6.7%
s72
 
5.4%
i72
 
5.4%
o72
 
5.4%
p54
 
4.0%
c54
 
4.0%
.54
 
4.0%
g54
 
4.0%
Other values (23)578
43.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter954
71.5%
Other Punctuation198
 
14.8%
Decimal Number164
 
12.3%
Connector Punctuation18
 
1.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t108
 
11.3%
a90
 
9.4%
s72
 
7.5%
i72
 
7.5%
o72
 
7.5%
p54
 
5.7%
c54
 
5.7%
g54
 
5.7%
m54
 
5.7%
e54
 
5.7%
Other values (9)270
28.3%
Decimal Number
ValueCountFrequency (%)
231
18.9%
829
17.7%
720
12.2%
617
10.4%
316
9.8%
115
9.1%
011
 
6.7%
910
 
6.1%
410
 
6.1%
55
 
3.0%
Other Punctuation
ValueCountFrequency (%)
/126
63.6%
.54
27.3%
:18
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin954
71.5%
Common380
 
28.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
t108
 
11.3%
a90
 
9.4%
s72
 
7.5%
i72
 
7.5%
o72
 
7.5%
p54
 
5.7%
c54
 
5.7%
g54
 
5.7%
m54
 
5.7%
e54
 
5.7%
Other values (9)270
28.3%
Common
ValueCountFrequency (%)
/126
33.2%
.54
14.2%
231
 
8.2%
829
 
7.6%
720
 
5.3%
:18
 
4.7%
_18
 
4.7%
617
 
4.5%
316
 
4.2%
115
 
3.9%
Other values (4)36
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII1334
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/126
 
9.4%
t108
 
8.1%
a90
 
6.7%
s72
 
5.4%
i72
 
5.4%
o72
 
5.4%
p54
 
4.0%
c54
 
4.0%
.54
 
4.0%
g54
 
4.0%
Other values (23)578
43.3%

_embedded.show.image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing53
Missing (%)100.0%
Memory size552.0 B

_embedded.show.network.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct6
Distinct (%)85.7%
Missing46
Missing (%)86.8%
Infinite0
Infinite (%)0.0%
Mean218.5714286
Minimum76
Maximum339
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size552.0 B
2022-09-05T21:41:59.961969image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum76
5-th percentile80.5
Q1138.5
median236
Q3301
95-th percentile339
Maximum339
Range263
Interquartile range (IQR)162.5

Descriptive statistics

Standard deviation107.1958599
Coefficient of variation (CV)0.4904385747
Kurtosis-1.498847118
Mean218.5714286
Median Absolute Deviation (MAD)103
Skewness-0.2694706665
Sum1530
Variance11490.95238
MonotonicityNot monotonic
2022-09-05T21:42:00.049755image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3392
 
3.8%
2631
 
1.9%
761
 
1.9%
2361
 
1.9%
911
 
1.9%
1861
 
1.9%
(Missing)46
86.8%
ValueCountFrequency (%)
761
1.9%
911
1.9%
1861
1.9%
2361
1.9%
2631
1.9%
3392
3.8%
ValueCountFrequency (%)
3392
3.8%
2631
1.9%
2361
1.9%
1861
1.9%
911
1.9%
761
1.9%

_embedded.show.network.name
Categorical

HIGH CORRELATION
MISSING

Distinct6
Distinct (%)85.7%
Missing46
Missing (%)86.8%
Memory size552.0 B
TV 2
TV Asahi
TV Tokyo
Oprah Winfrey Network
NRK1

Length

Max length21
Median length8
Mean length8
Min length4

Characters and Unicode

Total characters56
Distinct characters29
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)71.4%

Sample

1st rowTV 2
2nd rowTV 2
3rd rowTV Asahi
4th rowTV Tokyo
5th rowOprah Winfrey Network

Common Values

ValueCountFrequency (%)
TV 22
 
3.8%
TV Asahi1
 
1.9%
TV Tokyo1
 
1.9%
Oprah Winfrey Network1
 
1.9%
NRK11
 
1.9%
FUSE TV1
 
1.9%
(Missing)46
86.8%

Length

2022-09-05T21:42:00.135520image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:42:00.232045image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
tv5
35.7%
22
 
14.3%
asahi1
 
7.1%
tokyo1
 
7.1%
oprah1
 
7.1%
winfrey1
 
7.1%
network1
 
7.1%
nrk11
 
7.1%
fuse1
 
7.1%

Most occurring characters

ValueCountFrequency (%)
7
 
12.5%
T6
 
10.7%
V5
 
8.9%
o3
 
5.4%
r3
 
5.4%
h2
 
3.6%
i2
 
3.6%
k2
 
3.6%
y2
 
3.6%
22
 
3.6%
Other values (19)22
39.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter24
42.9%
Uppercase Letter22
39.3%
Space Separator7
 
12.5%
Decimal Number3
 
5.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o3
12.5%
r3
12.5%
h2
8.3%
i2
8.3%
k2
8.3%
y2
8.3%
a2
8.3%
e2
8.3%
s1
 
4.2%
w1
 
4.2%
Other values (4)4
16.7%
Uppercase Letter
ValueCountFrequency (%)
T6
27.3%
V5
22.7%
N2
 
9.1%
S1
 
4.5%
U1
 
4.5%
F1
 
4.5%
K1
 
4.5%
R1
 
4.5%
W1
 
4.5%
O1
 
4.5%
Other values (2)2
 
9.1%
Decimal Number
ValueCountFrequency (%)
22
66.7%
11
33.3%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin46
82.1%
Common10
 
17.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
T6
 
13.0%
V5
 
10.9%
o3
 
6.5%
r3
 
6.5%
h2
 
4.3%
i2
 
4.3%
k2
 
4.3%
y2
 
4.3%
a2
 
4.3%
e2
 
4.3%
Other values (16)17
37.0%
Common
ValueCountFrequency (%)
7
70.0%
22
 
20.0%
11
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII56
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7
 
12.5%
T6
 
10.7%
V5
 
8.9%
o3
 
5.4%
r3
 
5.4%
h2
 
3.6%
i2
 
3.6%
k2
 
3.6%
y2
 
3.6%
22
 
3.6%
Other values (19)22
39.3%

_embedded.show.network.country.name
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)42.9%
Missing46
Missing (%)86.8%
Memory size552.0 B
Norway
Japan
United States

Length

Max length13
Median length6
Mean length7.714285714
Min length5

Characters and Unicode

Total characters54
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNorway
2nd rowNorway
3rd rowJapan
4th rowJapan
5th rowUnited States

Common Values

ValueCountFrequency (%)
Norway3
 
5.7%
Japan2
 
3.8%
United States2
 
3.8%
(Missing)46
86.8%

Length

2022-09-05T21:42:00.320505image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:42:00.409678image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
norway3
33.3%
japan2
22.2%
united2
22.2%
states2
22.2%

Most occurring characters

ValueCountFrequency (%)
a9
16.7%
t6
11.1%
n4
 
7.4%
e4
 
7.4%
o3
 
5.6%
N3
 
5.6%
y3
 
5.6%
w3
 
5.6%
r3
 
5.6%
J2
 
3.7%
Other values (7)14
25.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter43
79.6%
Uppercase Letter9
 
16.7%
Space Separator2
 
3.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a9
20.9%
t6
14.0%
n4
9.3%
e4
9.3%
o3
 
7.0%
y3
 
7.0%
w3
 
7.0%
r3
 
7.0%
p2
 
4.7%
i2
 
4.7%
Other values (2)4
9.3%
Uppercase Letter
ValueCountFrequency (%)
N3
33.3%
J2
22.2%
U2
22.2%
S2
22.2%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin52
96.3%
Common2
 
3.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a9
17.3%
t6
11.5%
n4
 
7.7%
e4
 
7.7%
o3
 
5.8%
N3
 
5.8%
y3
 
5.8%
w3
 
5.8%
r3
 
5.8%
J2
 
3.8%
Other values (6)12
23.1%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII54
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a9
16.7%
t6
11.1%
n4
 
7.4%
e4
 
7.4%
o3
 
5.6%
N3
 
5.6%
y3
 
5.6%
w3
 
5.6%
r3
 
5.6%
J2
 
3.7%
Other values (7)14
25.9%

_embedded.show.network.country.code
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)42.9%
Missing46
Missing (%)86.8%
Memory size552.0 B
NO
JP
US

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters14
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNO
2nd rowNO
3rd rowJP
4th rowJP
5th rowUS

Common Values

ValueCountFrequency (%)
NO3
 
5.7%
JP2
 
3.8%
US2
 
3.8%
(Missing)46
86.8%

Length

2022-09-05T21:42:00.492533image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:42:00.580871image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
no3
42.9%
jp2
28.6%
us2
28.6%

Most occurring characters

ValueCountFrequency (%)
N3
21.4%
O3
21.4%
J2
14.3%
P2
14.3%
U2
14.3%
S2
14.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter14
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N3
21.4%
O3
21.4%
J2
14.3%
P2
14.3%
U2
14.3%
S2
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin14
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N3
21.4%
O3
21.4%
J2
14.3%
P2
14.3%
U2
14.3%
S2
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII14
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N3
21.4%
O3
21.4%
J2
14.3%
P2
14.3%
U2
14.3%
S2
14.3%

_embedded.show.network.country.timezone
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)42.9%
Missing46
Missing (%)86.8%
Memory size552.0 B
Europe/Oslo
Asia/Tokyo
America/New_York

Length

Max length16
Median length11
Mean length12.14285714
Min length10

Characters and Unicode

Total characters85
Distinct characters22
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEurope/Oslo
2nd rowEurope/Oslo
3rd rowAsia/Tokyo
4th rowAsia/Tokyo
5th rowAmerica/New_York

Common Values

ValueCountFrequency (%)
Europe/Oslo3
 
5.7%
Asia/Tokyo2
 
3.8%
America/New_York2
 
3.8%
(Missing)46
86.8%

Length

2022-09-05T21:42:00.662413image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:42:00.751303image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
europe/oslo3
42.9%
asia/tokyo2
28.6%
america/new_york2
28.6%

Most occurring characters

ValueCountFrequency (%)
o12
14.1%
r7
 
8.2%
e7
 
8.2%
/7
 
8.2%
s5
 
5.9%
i4
 
4.7%
A4
 
4.7%
k4
 
4.7%
a4
 
4.7%
u3
 
3.5%
Other values (12)28
32.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter60
70.6%
Uppercase Letter16
 
18.8%
Other Punctuation7
 
8.2%
Connector Punctuation2
 
2.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o12
20.0%
r7
11.7%
e7
11.7%
s5
8.3%
i4
 
6.7%
k4
 
6.7%
a4
 
6.7%
u3
 
5.0%
l3
 
5.0%
p3
 
5.0%
Other values (4)8
13.3%
Uppercase Letter
ValueCountFrequency (%)
A4
25.0%
E3
18.8%
O3
18.8%
T2
12.5%
N2
12.5%
Y2
12.5%
Other Punctuation
ValueCountFrequency (%)
/7
100.0%
Connector Punctuation
ValueCountFrequency (%)
_2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin76
89.4%
Common9
 
10.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
o12
15.8%
r7
 
9.2%
e7
 
9.2%
s5
 
6.6%
i4
 
5.3%
A4
 
5.3%
k4
 
5.3%
a4
 
5.3%
u3
 
3.9%
E3
 
3.9%
Other values (10)23
30.3%
Common
ValueCountFrequency (%)
/7
77.8%
_2
 
22.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII85
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o12
14.1%
r7
 
8.2%
e7
 
8.2%
/7
 
8.2%
s5
 
5.9%
i4
 
4.7%
A4
 
4.7%
k4
 
4.7%
a4
 
4.7%
u3
 
3.5%
Other values (12)28
32.9%

_embedded.show.network.officialSite
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing53
Missing (%)100.0%
Memory size552.0 B

_embedded.show.webChannel
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing53
Missing (%)100.0%
Memory size552.0 B

_embedded.show.webChannel.country
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing53
Missing (%)100.0%
Memory size552.0 B

Interactions

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2022-09-05T21:41:50.413779image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Correlations

2022-09-05T21:42:00.844509image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-09-05T21:42:01.079893image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-09-05T21:42:01.315335image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-09-05T21:42:01.586236image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-09-05T21:41:51.574404image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-09-05T21:41:52.197279image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-09-05T21:41:52.666586image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

idurlnameseasonnumbertypeairdateairtimeairstampruntimeimagesummaryrating.average_links.self.href_embedded.show.id_embedded.show.url_embedded.show.name_embedded.show.type_embedded.show.language_embedded.show.genres_embedded.show.status_embedded.show.runtime_embedded.show.averageRuntime_embedded.show.premiered_embedded.show.ended_embedded.show.officialSite_embedded.show.schedule.time_embedded.show.schedule.days_embedded.show.rating.average_embedded.show.weight_embedded.show.network_embedded.show.webChannel.id_embedded.show.webChannel.name_embedded.show.webChannel.country.name_embedded.show.webChannel.country.code_embedded.show.webChannel.country.timezone_embedded.show.webChannel.officialSite_embedded.show.dvdCountry_embedded.show.externals.tvrage_embedded.show.externals.thetvdb_embedded.show.externals.imdb_embedded.show.image.medium_embedded.show.image.original_embedded.show.summary_embedded.show.updated_embedded.show._links.self.href_embedded.show._links.previousepisode.href_embedded.show._links.nextepisode.hrefimage.mediumimage.original_embedded.show.image_embedded.show.network.id_embedded.show.network.name_embedded.show.network.country.name_embedded.show.network.country.code_embedded.show.network.country.timezone_embedded.show.network.officialSite_embedded.show.webChannel_embedded.show.webChannel.country
01988859https://www.tvmaze.com/episodes/1988859/sim-for-you-4x21-chanyeols-episode-21Chanyeol's Episode 21421regular2020-12-1206:002020-12-11T21:00:00+00:0016.0NaN<p><b>#LastNightOfSummerVacation #10PointsOutof10 #TheRevealoftheFinalGift</b></p>NaNhttps://api.tvmaze.com/episodes/198885941648https://www.tvmaze.com/shows/41648/sim-for-youSim for YouRealityKorean[]Running16.016.02019-03-25Nonehttps://www.vlive.tv/video/121637[Monday, Wednesday, Friday]NaN29NaN122.0V LIVEKorea, Republic ofKRAsia/Seoulhttps://www.vlive.tv/homeNoneNaN361541.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/190/476668.jpghttps://static.tvmaze.com/uploads/images/original_untouched/190/476668.jpg<p><b>Sim for You</b> is a reality series that chronicles each EXO member's life and reveal stories from their everyday life as a series.</p>1608499007https://api.tvmaze.com/shows/41648https://api.tvmaze.com/episodes/1988862NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
11986140https://www.tvmaze.com/episodes/1986140/soul-land-7x04-di134ji第134集74regular2020-12-1210:002020-12-12T02:00:00+00:0020.0NaNNoneNaNhttps://api.tvmaze.com/episodes/198614035551https://www.tvmaze.com/shows/35551/soul-landSoul LandAnimationChinese[Action, Adventure, Anime, Fantasy]Running20.020.02018-01-13Nonehttps://v.qq.com/detail/m/m441e3rjq9kwpsc.html10:00[Saturday]7.791NaN104.0Tencent QQChinaCNAsia/Shanghaihttps://v.qq.com/NoneNaN342329.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/150/375304.jpghttps://static.tvmaze.com/uploads/images/original_untouched/150/375304.jpg<p>Tang San spent his life in the Tang Outer Sect, dedicated to the creation and mastery of hidden weapons. Once he stole the secret lore of the Inner Sect to reach the pinnacle of his art, his only way out was death. But after throwing himself off the deadly Hell's Peak he was reborn in a different world, the world of Douluo Dalu, a world where every person has a spirit of their own, and those with powerful spirits can practice their spirit power to rise and become Spirit Masters.<br /><br />The spirit that awakens within Tang San is Blue Silver Grass, a useless spirit. Can he overcome the difficulties to reach the high ranks of Spirit Masters and bring the glory of the Tang Sect into this new world?</p>1652939782https://api.tvmaze.com/shows/35551https://api.tvmaze.com/episodes/2330393https://api.tvmaze.com/episodes/2330394NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
22386106https://www.tvmaze.com/episodes/2386106/xian-feng-jian-yu-lu-1x47-episode-47Episode 47147regular2020-12-1210:002020-12-12T02:00:00+00:008.0NaNNoneNaNhttps://api.tvmaze.com/episodes/238610649206https://www.tvmaze.com/shows/49206/xian-feng-jian-yu-luXian Feng Jian Yu LuAnimationChinese[Action, Anime, Fantasy, Supernatural]Running8.07.02020-07-11Nonehttps://v.qq.com/detail/m/mzc00200hc38s5x.html10:00[Wednesday, Saturday]NaN62NaN104.0Tencent QQChinaCNAsia/Shanghaihttps://v.qq.com/NoneNaN386423.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/270/675333.jpghttps://static.tvmaze.com/uploads/images/original_untouched/270/675333.jpg<p>In ancient Shenzhou, humans and demons had been in constant dispute for thousands of years. The demon princess from Tushan, Bai Binglan, and the human Zhang Kuangyun met each other due to a misunderstanding. In order to investigate the enemy country, Bai Binglan became Zhang Kuangyun's companion. As they travel together, Zhang Kuangyun discovers a conspiracy...</p>1662275668https://api.tvmaze.com/shows/49206https://api.tvmaze.com/episodes/2386129NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
32138925https://www.tvmaze.com/episodes/2138925/tokyo-joshi-pro-wrestling-2020-12-12-tjpw-fall-tour-20-womm-wrestling-of-my-mindTJPW Fall Tour '20 ~ WOMM (Wrestling Of My Mind) ~202043regular2020-12-1212:002020-12-12T03:00:00+00:00120.0NaNNoneNaNhttps://api.tvmaze.com/episodes/213892549740https://www.tvmaze.com/shows/49740/tokyo-joshi-pro-wrestlingTokyo Joshi Pro WrestlingSportsJapanese[]Running120.0120.02013-01-30Nonehttps://www.ddtpro.com/12:00[Saturday]NaN46NaN408.0DDTUniverseJapanJPAsia/TokyoNoneNoneNaN375304.0tt10784214https://static.tvmaze.com/uploads/images/medium_portrait/268/670796.jpghttps://static.tvmaze.com/uploads/images/original_untouched/268/670796.jpgNone1661106712https://api.tvmaze.com/shows/49740https://api.tvmaze.com/episodes/2377377https://api.tvmaze.com/episodes/2377378NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
41962057https://www.tvmaze.com/episodes/1962057/heaven-officials-blessing-1x08-foreboding-wind-of-the-ancient-countryForeboding Wind of the Ancient Country18regular2020-12-1211:002020-12-12T03:00:00+00:0025.0NaNNoneNaNhttps://api.tvmaze.com/episodes/196205751670https://www.tvmaze.com/shows/51670/heaven-officials-blessingHeaven Official's BlessingAnimationChinese[Drama, Anime, Fantasy, Romance]Running25.025.02020-10-31Nonehttps://www.bilibili.com/tgcf11:00[Saturday]7.344NaN51.0BilibiliChinaCNAsia/ShanghaiNoneNoneNaN388672.0tt13375866https://static.tvmaze.com/uploads/images/medium_portrait/414/1036502.jpghttps://static.tvmaze.com/uploads/images/original_untouched/414/1036502.jpg<p>"Have you heard? The rubbish Heaven Official is having an affair with the ghost realm's number one bigshot!"</p><p>Eight hundred years ago, Xie Lian was the Crown Prince of the Xian Le kingdom; one who was beloved by his citizens and the darling of the world. Unsurprisingly, he ascended to the Heavens at a very young age. Now, eight hundred years later, Xie Lian ascends to the Heavens for the third time as the laughing stock of all three realms. On his first task as a god, he meets a mysterious demon who rules the ghosts and terrifies the Heavens... yet unbeknownst to Xie Lian, this demon king has been paying attention to him for a very, very long time.</p>1656761777https://api.tvmaze.com/shows/51670https://api.tvmaze.com/episodes/1993891NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
51972565https://www.tvmaze.com/episodes/1972565/the-wolf-1x23-episode-23Episode 23123regular2020-12-122020-12-12T04:00:00+00:0045.0NaNNoneNaNhttps://api.tvmaze.com/episodes/197256547912https://www.tvmaze.com/shows/47912/the-wolfThe WolfScriptedChinese[Drama, Romance, History]Ended45.045.02020-11-192021-01-04https://www.iqiyi.com/lib/m_213579814.html[]NaN38NaN118.0YoukuChinaCNAsia/ShanghaiNoneNoneNaN331095.0tt8871128https://static.tvmaze.com/uploads/images/medium_portrait/255/639532.jpghttps://static.tvmaze.com/uploads/images/original_untouched/255/639532.jpg<p>The story happens at the end of the Tang Dynasty, when Zhu Wen usurps the throne and establishes the Later Liang Dynasty, and he's known as Emperor Taizu. Ma Zhai Xing (Li Qin) is the daughter of an official and as a child, she befriends a young boy (Darren Wang) who lives in the mountain. One day when he saves a wolf, he accidentally falls over the cliff and is rescued by Zhu Wen. The authoritative figure adopts him as a godson and gives him the title Bo Wang. Ten years later, he saves the female lead per chance and finds her courage and intelligence resonant, and she likes that while he's in a position of power, he still has humility and kindness. She encourages him to fight for justice and he begins that journey by helping the people, stopping throne fights, etc. Even when they have conflicts, they will face those frankly. As they overcome obstacles and fight for justice, feelings deepen and they are able to reap their own happiness by each other's side.</p>1648217029https://api.tvmaze.com/shows/47912https://api.tvmaze.com/episodes/1972591NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
61972566https://www.tvmaze.com/episodes/1972566/the-wolf-1x24-episode-24Episode 24124regular2020-12-122020-12-12T04:00:00+00:0045.0NaNNoneNaNhttps://api.tvmaze.com/episodes/197256647912https://www.tvmaze.com/shows/47912/the-wolfThe WolfScriptedChinese[Drama, Romance, History]Ended45.045.02020-11-192021-01-04https://www.iqiyi.com/lib/m_213579814.html[]NaN38NaN118.0YoukuChinaCNAsia/ShanghaiNoneNoneNaN331095.0tt8871128https://static.tvmaze.com/uploads/images/medium_portrait/255/639532.jpghttps://static.tvmaze.com/uploads/images/original_untouched/255/639532.jpg<p>The story happens at the end of the Tang Dynasty, when Zhu Wen usurps the throne and establishes the Later Liang Dynasty, and he's known as Emperor Taizu. Ma Zhai Xing (Li Qin) is the daughter of an official and as a child, she befriends a young boy (Darren Wang) who lives in the mountain. One day when he saves a wolf, he accidentally falls over the cliff and is rescued by Zhu Wen. The authoritative figure adopts him as a godson and gives him the title Bo Wang. Ten years later, he saves the female lead per chance and finds her courage and intelligence resonant, and she likes that while he's in a position of power, he still has humility and kindness. She encourages him to fight for justice and he begins that journey by helping the people, stopping throne fights, etc. Even when they have conflicts, they will face those frankly. As they overcome obstacles and fight for justice, feelings deepen and they are able to reap their own happiness by each other's side.</p>1648217029https://api.tvmaze.com/shows/47912https://api.tvmaze.com/episodes/1972591NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
71998578https://www.tvmaze.com/episodes/1998578/mr-right-is-here-1x07-episode-7Episode 717regular2020-12-122020-12-12T04:00:00+00:0045.0NaNNoneNaNhttps://api.tvmaze.com/episodes/199857852782https://www.tvmaze.com/shows/52782/mr-right-is-hereMr. Right is Here!ScriptedChinese[Drama, Comedy, Romance]Ended45.045.02020-12-102020-12-18None[Thursday, Friday, Saturday]NaN14NaN118.0YoukuChinaCNAsia/ShanghaiNoneNoneNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/291/729462.jpghttps://static.tvmaze.com/uploads/images/original_untouched/291/729462.jpg<p>‎The fashion company faced a crisis. Sun Chi, the young owner of the company, at a critical moment took over the management and became the new CEO. He promised his father that in three months he would be able to promote the project "promoting fashion" that will help to get out of the crisis. ‎ </p><p>‎Gio Intao, who wanted to be the queen of the fashion industry, by coincidence got into the company and became subordinate to the "devil", a young gene. Director Sun Chi.‎   </p><p>‎Sun Chi and Xiao Intao led a fashion company to resolve the crisis and open new markets, allowing Chinese fashion brands to enter the global market step by step. At the same time, they begin to feel each other.‎</p>1609671640https://api.tvmaze.com/shows/52782https://api.tvmaze.com/episodes/1998584NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
81998579https://www.tvmaze.com/episodes/1998579/mr-right-is-here-1x08-episode-8Episode 818regular2020-12-122020-12-12T04:00:00+00:0045.0NaNNoneNaNhttps://api.tvmaze.com/episodes/199857952782https://www.tvmaze.com/shows/52782/mr-right-is-hereMr. Right is Here!ScriptedChinese[Drama, Comedy, Romance]Ended45.045.02020-12-102020-12-18None[Thursday, Friday, Saturday]NaN14NaN118.0YoukuChinaCNAsia/ShanghaiNoneNoneNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/291/729462.jpghttps://static.tvmaze.com/uploads/images/original_untouched/291/729462.jpg<p>‎The fashion company faced a crisis. Sun Chi, the young owner of the company, at a critical moment took over the management and became the new CEO. He promised his father that in three months he would be able to promote the project "promoting fashion" that will help to get out of the crisis. ‎ </p><p>‎Gio Intao, who wanted to be the queen of the fashion industry, by coincidence got into the company and became subordinate to the "devil", a young gene. Director Sun Chi.‎   </p><p>‎Sun Chi and Xiao Intao led a fashion company to resolve the crisis and open new markets, allowing Chinese fashion brands to enter the global market step by step. At the same time, they begin to feel each other.‎</p>1609671640https://api.tvmaze.com/shows/52782https://api.tvmaze.com/episodes/1998584NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
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432042787https://www.tvmaze.com/episodes/2042787/ufc-fight-pass-prelims-2020-12-12-ufc-256-figueiredo-vs-moreno-early-prelimsUFC 256: Figueiredo vs. Moreno Early Prelims202052regular2020-12-122020-12-12T17:00:00+00:0060.0NaNNoneNaNhttps://api.tvmaze.com/episodes/204278725294https://www.tvmaze.com/shows/25294/ufc-fight-pass-prelimsUFC Fight Pass PrelimsSportsEnglish[]Running60.074.02017-01-15Nonehttps://www.ufc.tv/page/fightpass[Saturday]NaN39NaN45.0UFC Fight PassUnited StatesUSAmerica/New_YorkNoneNoneNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/398/996679.jpghttps://static.tvmaze.com/uploads/images/original_untouched/398/996679.jpg<p>Televised undercard bouts from UFC Pay-Per-Views and UFC Fight Nights exclusively on UFC Fight Pass.</p>1646528986https://api.tvmaze.com/shows/25294https://api.tvmaze.com/episodes/2230458NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
442042788https://www.tvmaze.com/episodes/2042788/ufc-fight-pass-prelims-2020-12-12-ufc-256-figueiredo-vs-moreno-prelimsUFC 256: Figueiredo vs. Moreno Prelims202053regular2020-12-122020-12-12T17:00:00+00:0060.0NaNNoneNaNhttps://api.tvmaze.com/episodes/204278825294https://www.tvmaze.com/shows/25294/ufc-fight-pass-prelimsUFC Fight Pass PrelimsSportsEnglish[]Running60.074.02017-01-15Nonehttps://www.ufc.tv/page/fightpass[Saturday]NaN39NaN45.0UFC Fight PassUnited StatesUSAmerica/New_YorkNoneNoneNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/398/996679.jpghttps://static.tvmaze.com/uploads/images/original_untouched/398/996679.jpg<p>Televised undercard bouts from UFC Pay-Per-Views and UFC Fight Nights exclusively on UFC Fight Pass.</p>1646528986https://api.tvmaze.com/shows/25294https://api.tvmaze.com/episodes/2230458NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
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481967068https://www.tvmaze.com/episodes/1967068/maskorama-1x06-episode-6Episode 616regular2020-12-1219:502020-12-12T18:50:00+00:0089.0NaN<p>Finale! The last three participants will go through the finals and gold finals. Tonight we are left with one winner and three revelations! Did you guess correctly?</p>NaNhttps://api.tvmaze.com/episodes/196706851314https://www.tvmaze.com/shows/51314/maskoramaMaskoramaRealityNorwegian[Music]Running90.088.02020-11-07Nonehttps://tv.nrk.no/serie/maskorama19:50[Saturday]NaN22NaN238.0NRK TVNorwayNOEurope/OsloNoneNoneNaN391528.0tt13510734https://static.tvmaze.com/uploads/images/medium_portrait/370/926987.jpghttps://static.tvmaze.com/uploads/images/original_untouched/370/926987.jpg<p>Based on the international hit "The Masked Singer", in <b>Maskorama </b>eight elebrities will face off against one another with a twist: each singer is using masks and costumes, the judges panel will have to guess which celebrity is behind the mask.</p>1640454812https://api.tvmaze.com/shows/51314https://api.tvmaze.com/episodes/2207405NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/288/722361.jpghttps://static.tvmaze.com/uploads/images/original_untouched/288/722361.jpgNaN91.0NRK1NorwayNOEurope/OsloNaNNaNNaN
491982435https://www.tvmaze.com/episodes/1982435/onyx-equinox-1x04-the-strangerThe Stranger14regular2020-12-1216:002020-12-12T21:00:00+00:0024.0NaN<p>lzel, K'in and Yun head towards the second gate at Lakamha, where they encounter a warrior looking to bargain.</p>8.0https://api.tvmaze.com/episodes/198243548922https://www.tvmaze.com/shows/48922/onyx-equinoxOnyx EquinoxAnimationEnglish[Action, Adventure, Fantasy]Ended24.024.02020-11-212020-12-26https://www.crunchyroll.com/onyx-equinox16:00[Saturday]5.046NaN20.0CrunchyrollNaNNaNNaNNoneNoneNaN377625.0tt12605636https://static.tvmaze.com/uploads/images/medium_portrait/263/658930.jpghttps://static.tvmaze.com/uploads/images/original_untouched/263/658930.jpg<p>A young Aztec boy is saved from death by the gods and chosen to act as ‘humanity's champion,' forced to discard his apathy toward his fellow man and prove humanity's potential in a fight that spans across fantastical-yet-authentic Mesoamerican cultures.</p>1609359827https://api.tvmaze.com/shows/48922https://api.tvmaze.com/episodes/1990352NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
501972346https://www.tvmaze.com/episodes/1972346/eides-spraksjov-6x04-trompetvokabularetTrompetvokabularet64regular2020-12-1222:152020-12-12T21:15:00+00:0045.0NaNNoneNaNhttps://api.tvmaze.com/episodes/197234651631https://www.tvmaze.com/shows/51631/eides-spraksjovEides språksjovTalk ShowNorwegian[Comedy]RunningNaN43.02017-01-11Nonehttps://tv.nrk.no/serie/eides-spraaksjov[Saturday]NaN4NaN238.0NRK TVNorwayNOEurope/OsloNoneNoneNaN322906.0tt8851444https://static.tvmaze.com/uploads/images/medium_portrait/280/701389.jpghttps://static.tvmaze.com/uploads/images/original_untouched/280/701389.jpg<p>Entertainment from here to the moon when Linda Eide and guests pay tribute and joke with language.</p>1650016918https://api.tvmaze.com/shows/51631https://api.tvmaze.com/episodes/2297850NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
511982904https://www.tvmaze.com/episodes/1982904/the-streamy-awards-2020-12-12-the-10th-annual-streamy-awardsThe 10th Annual Streamy Awards20201regular2020-12-1221:002020-12-13T02:00:00+00:0095.0NaN<p>Join hosts Trixie and Katya for the 2020 YouTube Streamy Awards as we honor the best of our creator community. Watch it free December 12 with ads on YouTube or sign up for YouTube Premium to watch exclusive Q&amp;As with Streamys creators that you won't find anywhere else.</p>NaNhttps://api.tvmaze.com/episodes/19829043734https://www.tvmaze.com/shows/3734/the-streamy-awardsThe Streamy AwardsAward ShowEnglish[]Running90.0108.02009-03-28Nonehttp://www.streamys.org21:00[Saturday]NaN37NaN21.0YouTubeNaNNaNNaNhttps://www.youtube.comNoneNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/264/662342.jpghttps://static.tvmaze.com/uploads/images/original_untouched/264/662342.jpg<p><b>The Streamy Awards </b>honor the best in online video and the creators behind it. The annual event brings together the biggest names in YouTube and online video for a night of celebration, discovery, and meaningful recognition.</p>1615235438https://api.tvmaze.com/shows/3734https://api.tvmaze.com/episodes/1982904NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/288/721362.jpghttps://static.tvmaze.com/uploads/images/original_untouched/288/721362.jpgNaN186.0FUSE TVUnited StatesUSAmerica/New_YorkNaNNaNNaN
522042203https://www.tvmaze.com/episodes/2042203/cage-warriors-2020-12-12-cage-warriors-119Cage Warriors 11920208regular2020-12-1221:002020-12-13T02:00:00+00:00120.0NaNNoneNaNhttps://api.tvmaze.com/episodes/204220350594https://www.tvmaze.com/shows/50594/cage-warriorsCage WarriorsSportsEnglish[]Running120.0120.02002-07-27Nonehttps://cagewarriors.com21:00[Friday]NaN6NaN45.0UFC Fight PassUnited StatesUSAmerica/New_YorkNoneNoneNaN388898.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/401/1004364.jpghttps://static.tvmaze.com/uploads/images/original_untouched/401/1004364.jpg<p><b>Cage Warriors</b> is a mixed martial arts promotion, based in London. The promotion was established in 2001 and staged its first MMA event in London in July, 2002. </p>1659372851https://api.tvmaze.com/shows/50594https://api.tvmaze.com/episodes/2369043NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/402/1005471.jpghttps://static.tvmaze.com/uploads/images/original_untouched/402/1005471.jpgNaNNaNNaNNaNNaNNaNNaNNaNNaN